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About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The Product In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale. The Role We are looking for a Senior Software Engineer to build the web access infrastructure behind a novel search engine designed for agentic AI. In this role, you will investigate how modern websites communicate with browsers and translate that understanding into production systems operating at internet scale. You will build browser infrastructure and tooling that enables reliable, efficient access to web content across a rapidly changing web. Your responsibilities will include: Research and analyse how modern websites communicate with browsers across the complete request lifecycle Investigate browser fingerprinting, client verification mechanisms, and modern web technologies to enable reliable web access Build tooling for browser instrumentation, debugging, observability, and large-scale experimentation Translate technical research into production systems operating at internet scale Requirements You have 5+ years of experience as a software engineer working on production backend or infrastructure systems, and are an expert in several of the following areas: Browser Technologies Chromium architecture and browser internals Browser lifecycle and navigation Chrome DevTools Protocol (CDP) Playwright, Puppeteer, Selenium, or similar browser automation frameworks Browser instrumentation and debugging Web Platform HTTP/1.1, HTTP/2, HTTP/3 — TLS, DNS, and browser networking Cookies, browser storage, caching, redirects, and session management JavaScript execution and modern client-side rendering Resource loading, page lifecycle, and browser networking Browser fingerprinting concepts and browser characteristics Nice to Have Experience working on browser engines or browser infrastructure Experience reverse engineering browser or web application behaviour Experience building internet-scale distributed systems Go, C++, Rust, or Python Kubernetes and cloud infrastructure We conduct coding interviews as part of the process. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know. Find Jobs in Switzerland on Arbeitnow

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. We are seeking a Staff Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems. You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. What you'll work on: Designing agent native retrieval systems optimised for machine consumption rather than human search UX Building systems where LLMs iteratively plan, query, refine, and reason over results Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints Your responsibilites: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) Develop methods for grounding LLMs in real time web data at scale Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production Analyse trade-offs across relevance, latency, and cost at scale Work closely with engineering to deploy systems in high throughput, low latency environments Own ambiguous problems end to end and contribute to product and research direction Mentor engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking, recommendation systems, or assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM integrated or knowledge intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python and at least one of Go, C++, or similar Ability to operate in a fast moving, product driven environment with high ownership and autonomy Nice to haves Experience with large scale search or recommendation systems Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RAG, multi step retrieval, or tool use Publications, open source, or similar signals of technical depth and impact Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know. Find Jobs in Switzerland on Arbeitnow

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The Product In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale. The Role We are looking for a Staff Software Engineer to work on the content acquisition and crawling infrastructure of a novel search engine tailored for agentic AI consumption. In this role, you will focus on building systems that discover, fetch, and continuously refresh content from the open web and other large-scale data sources. You will design distributed crawling, scheduling, and ingestion infrastructure capable of operating at internet scale while balancing coverage, freshness, resource efficiency, and reliability. You will work on systems that process billions of URLs, manage high-throughput data flows, and ensure that high-quality content is consistently available to downstream indexing and retrieval systems. In this position, your responsibility will be to: Design, implement, and operate web-scale crawling systems for acquiring content from the internet Build ingestion workflows for internal and external data sources, including crawlers, structured feeds, and partner integrations Develop crawl scheduling, prioritisation, recrawl policies, and freshness strategies Build systems for URL discovery, deduplication, content extraction, and crawl orchestration Ensure reliable operation of crawling infrastructure under high-throughput conditions Define observability and quality metrics for crawl coverage, freshness, throughput, and content quality Monitor resource usage, bandwidth consumption, and infrastructure cost Collaborate with indexing and ML teams to ensure acquired content meets retrieval and ranking requirements Enable safe experimentation with crawling strategies and content acquisition policies You may be a good fit if you: 8+ years of experience building backend or distributed systems Strong Go or C++ expertise Experience with large-scale distributed systems (10k+ RPS, billions of URLs, high-throughput pipelines) Understanding of web protocols (HTTP, DNS, TLS), crawling, scraping, and content extraction Experience operating production systems and debugging failures in distributed environments Strong understanding of scalability, fault tolerance, and resource management Strong candidates may also have experience with: Web crawling Building streaming data pipelines and event-driven systems Kafka, Pulsar, NATS, RabbitMQ, or similar messaging platforms Designing distributed schedulers, queues, and asynchronous processing systems Spark, Flink, Beam, or MapReduce Ad tech, social networks, search engines, or other large-scale content platforms We conduct coding interviews as part of the process. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know. Find more English Speaking Jobs in Switzerland on Arbeitnow

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The Product In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale. The Role We are looking for a Staff Software Engineer to work on the runtime systems of a novel search engine tailored for agentic AI consumption. In this role, you will focus on building low-latency, high-throughput systems that serve search queries in real time. You will work on the critical path of user-facing requests, where performance, predictability, and efficiency directly impact product quality. You will design and operate systems that handle thousands of requests per second under strict latency budgets, optimising every layer from request handling to data access and response assembly. In this position, your responsibility will be to Design, implement, and operate core runtime services for serving search queries at scale Build and optimise request flows, including query processing, retrieval orchestration, and response assembly under strict latency budgets Develop systems that maintain performance and predictability under high load Optimise CPU, memory, and data access patterns in performance-critical paths Ensure reliability, observability, and predictability across production services Build well-tested systems with clear responsibilities and interaction contracts, while remaining flexible as architecture evolves Define and implement observability primitives, including structured logs, metrics, traces, and latency breakdowns Monitor throughput, latency, and resource usage, and drive improvements in performance and cost efficiency Collaborate with indexing and ML teams to integrate retrieval and ranking components, keeping ML logic decoupled from core system internals Support experimentation and iteration through controlled rollouts and rigorous benchmarking You may be a good fit if you: Have 8+ years of experience as a software engineer working on production backend systems Have strong hands-on expertise in C++ or Rust in real-world, high-load services Have built and operated high-load, low-latency user-facing systems handling thousands of RPS under strict latency constraints Understand performance at a systems level — CPU, memory, networking, and data access Have operated your own code in production: deployed it, debugged incidents, and rolled back changes when necessary Think end-to-end about request flows rather than staying within isolated components Can balance correctness, latency, and development velocity, making pragmatic tradeoffs when scope or time requires Collaborate effectively across engineering, ML, and product teams, communicating clearly in cross-functional settings Strong candidates may also have experience with: DBMS internals (open source or SaaS) and cloud infrastructure High-load web applications or large-scale APIs Performance-critical systems such as trading platforms or real-time data pipelines Low-level performance tuning and hardware-level optimisation Open-source contributions or active involvement in the engineering community Competitive programming or CTF participation SHAD or similar advanced technical programmes Conference talks or technical publications We conduct coding interviews as part of the process. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know. Find Jobs in Switzerland on Arbeitnow

Dans le cadre de l'ouverture d'un poste en CDI, nous recrutons un.e AI engineer (f/m/d) , basé-e à Paris. 🚀 CONTEXTE & ENJEUX STRATÉGIQUES Au sein de Decathlon Digital, l'équipe People Data engage une initiative majeure : transformer l'expérience de nos 100 000 collaborateurs par l'intégration de l'IA Générative et Agentique. Face à la fragmentation de l'écosystème RH dans plus de 70 pays, notre ambition est de construire une couche de simplification en s'appuyant sur les nouvelles solutions que proposent l'IA. Il s'agit d'une couche d'intelligence centralisée et agnostique des outils, capable d'interagir avec l'ensemble de notre infrastructure (Workday, Data Lake, University, ...) pour faire évoluer nos interfaces d'une logique de consultation vers une logique d'action. Dans ce cadre, nous développons DaiLY , notre agent conversationnel RH. Il aide nos collaborateurs et managers à accéder instantanément à une information fiable, sourcée à partir de notre documentation Workday et de nos politiques People. Déjà déployé avec succès en France, DaiLY entre dans une nouvelle phase de passage à l'échelle : extension internationale, industrialisation des évaluations, amélioration continue de nos modèles et de leurs qualités et déploiement et intégration d'agents autonomes RH. Pour mener ce projet, nous ne recherchons pas uniquement un.e développeur.se, nous avons besoin d'un.e " Builder " : un.e personne capable de traduire un besoin métier en solution technique, de l'implémenter, la qualifier, la déployer et la maintenir dans le temps. 🎯 VOTRE MISSION Nous recherchons un(e) AI Engineer confirmé(e) pour participer activement à l'industrialisation et au développement de DaiLY. Votre objectif est clair : transformer les besoins métiers RH en fonctionnalités IA fiables, mesurables et robustes. Pour relever ce défi, vous évoluerez au sein d'un collectif dédié , en collaboration directe avec d'autres AI Engineers, un Lead AI Engineer (qui orientera les choix d'architecture globale) et une Product Manager. Cette organisation de proximité vous permettra d'assurer une synergie parfaite entre les enjeux produits, la roadmap et l'implémentation technique. Vous aurez notamment un rôle clé dans l'évolution de DaiLY : passer d'un modèle de simple consultation (Q&A) à un véritable système agentique transactionnel capable de déclencher des actions concrètes (ex : poser des congés dans Workday, s'inscrire à des formations via Decathlon University). 🛠 VOS RESPONSABILITES Développement Agentique & Fonctionnalités Participer à l'extension des capacités de DaiLY vers des actions d'écriture (write actions) en implémentant des protocoles de tool-calling (MCP - Model Context Protocol) et des communications inter-agents (A2A). Implémenter des stratégies avancées de chunking et de re-ranking pour prioriser les règles spécifiques au domaine RH. Contribuer à l'optimisation des coûts, de la latence et de l'efficacité globale du système en lien avec les équipes Plateforme et Infrastructure. Qualité, Évaluation & Observabilité (LLMOps) Développer et maintenir la couche de qualité du pipeline RAG multi-agents (Vertex AI Search / Discovery Engine). Assurer le grounding (ancrage) des réponses et la vérification des citations pour garantir la traçabilité vers une source de vérité. Mettre en place des pipelines d'observabilité robustes pour l'évaluation online et offline (OpenTelemetry, MLflow). Coder des évaluateurs automatiques basés sur des golden datasets pour itérer sereinement et prévenir les régressions avant chaque mise en production. Intégrer des garde-fous (guardrails) pour protéger le système et les utilisateurs contre les hallucinations et les erreurs. Sécurité, Cloisonnement & Déploiement International Access Management (ACLs) : Implémenter une gestion granulaire et dynamique des droits d'accès au niveau de l'indexation et du retrieval, garantissant qu'un collaborateur n'accède strictement qu'aux documents RH de son périmètre. Isolation & Multi-tenancy : Mettre en œuvre des stratégies de filtrage par métadonnées (metadata filtering) en base vectorielle et de cloisonnement (des index et/ou des modèles) pour assurer une étanchéité parfaite des données entre les différentes sociétés fiscales, entités légales et géographies de Decathlon. Support Multilingue : Contribuer à l'architecture d'internationalisation de DaiLY en adaptant les pipelines RAG, l'embedding et l'inférence pour maintenir un haut niveau de performance et de pertinence sur une grande diversité de langues. Produit & Impact Business Aider à l'analyse des intentions des utilisateurs pour mesurer l'impact de DaiLY. Traduire, avec l'appui de la Product Manager et du Lead, les enjeux métier en comportements de modèles et en métriques de succès. 🧠 PROFIL RECHERCHE Nous recherchons un profil justifiant a minima d'une première expérience. Expérience : Profil confirmé justifiant de trois années d'expérience professionnelle en entreprise (hors stages et alternances) en AI Engineering, ML Engineering ou Software Engineering orienté IA. Vous justifiez également d'au moins une expérience concrète et réussie de mise en production d'un système GenAI ou agentique. Stack Technique : Solide maîtrise de Python, de l'écosystème GCP / Vertex AI, et des frameworks d'orchestration (LangChain, LlamaIndex ou ADK). Expertise LLM & Agentique : Solide maîtrise des architectures RAG (recherche vectorielle, Vertex AI Vector Search, gestion avancée de métadonnées), mais surtout des concepts techniques agentiques : function/tool-calling, boucles de raisonnement (ReAct, etc.), orchestration de workflows multi-agents, structured output et gestion du contexte/mémoire. Qualité & Évaluation : Capacité à diagnostiquer une réponse incorrecte (problème de modèle, de retrieval ou de données) et appétence pour l'observabilité applicative (SQL / BigQuery / MLflow). Langues : Français courant obligatoire & anglais professionnel courant (environnement international). Les plus : Connaissance technique approfondie des protocoles A2A (Agent-to-Agent) et MCP. Expérience de traitement multimodal de documents ou dans des écosystèmes SIRH (ex: Workday). Compréhension technique des enjeux de sécurité (RBAC, ACLs, RGPD) appliqués aux LLMs. Connaissance des architectures microservices et conception d'APIs. 🎁 CE QUE NOUS PROPOSONS L'opportunité de développer un produit d'IA agentique de pointe avec un impact direct sur le quotidien de 100 000 collaborateurs. Un environnement technologique premium (Stack Google Cloud / Vertex AI / Databricks). Une politique de télétravail flexible (2 jours par semaine en remote, le reste dans nos bureaux à Paris - Canal de l'Ourcq). Une culture du delivery axée sur l'autonomie, l'intelligence collective et la montée en compétences (accompagnement par un Lead, certifications, formations). Des avantages attractifs (primes mensuelles/trimestrielles, actionnariat salarié). Une ambiance résolument tournée vers le sport (nombreuses corpos, tests produits, pauses déjeuner sportives ou non, …) DECATHLON DIGITAL Imaginez si la technologie nous permettait de repousser les frontières et d'offrir des expériences sportives inédites. C'est précisément notre ambition chez Decathlon Digital ! Nous sommes une équipe de plus de 5 000 experts en ingénierie logicielle, gestion de produits, données, cloud et cybersécurité, répartis à Paris, Lille et Amsterdam. Ensemble, nous créons la plus vaste plateforme sportive numérique, en exploitant les innovations technologiques pour optimiser la chaîne de valeur, concevoir des expériences connectées et donner une seconde vie à nos produits. Changeons la donne pour de bon. Notre passion du sport nous guide et nous voulons qu'elle perdure. C'est pourquoi nous nous engageons à bâtir un modèle technologique plus durable, en réduisant notre impact direct sur l'environnement, et en créant un espace sûr et inclusif pour apprendre et nous épanouir ensemble. Rejoins l'équipe et façonnons le futur du sport. Find more English Speaking Jobs in France on Arbeitnow

L'équipe Price Hub recrute à Nantes : rejoins-nous comme Software Engineer Java/Kafka ! 7 millions d'événements Kafka par jour, des pics à plusieurs dizaines de millions, avec un objectif clair : zéro perte. Tu nous aides à tenir ce cap ? Chaque jour, dans plus de 2 000 magasins et plus de 70 pays, des millions de prix changent. Une erreur, c'est un client mal servi, un magasin en difficulté et de la confiance perdue. Notre rôle : identifier et transmettre le bon prix, au bon moment, sans erreur, partout dans le monde. Nos 2 produits critiques tournent 24/7, avec un SLA supérieur à 99,9 %. Autour d'eux, 4 autres produits exploitent les données de vente et proposent des leviers de dynamisme commercial aux magasins. Tu rejoindras une plateforme event-driven qui évolue en continu pour répondre à des enjeux de performance, de résilience et de qualité. Au sein de l'équipe, tu contribueras concrètement à cette ambition en développant et en faisant évoluer nos produits. TA FUTURE CONTRIBUTION Tu conçois, développes et maintiens des fonctionnalités backend en Java ou Kotlin, en lien avec les besoins produit. Tu participes à la conception de solutions robustes pour nos systèmes distribués et nos flux Kafka. Tu contribues à la qualité du code par les tests, les revues de code et le partage de bonnes pratiques. Tu prends part aux décisions techniques de l'équipe et documentes les choix importants. Tu participes à l'amélioration continue de la performance, de l'observabilité et de la résilience de nos services. Tu contribues à l'exploitation de nos produits en production : investigation, suivi des alertes et résolution des incidents, avec le soutien de l'équipe. Tu travailles en étroite collaboration avec les Software Engineers, le Product Manager, l'Engineering Manager, le QE et le Support Engineer. STACK TECHNIQUE Java, Kotlin Kafka, architecture event-driven, microservices, APIs REST PostgreSQL, Valkey (cache) Docker, Kubernetes GitHub Actions (CI), Flux (GitOps / CD) Datadog (monitoring et alerting) Bonus : React CE QUE TU APPORTES Une expérience significative en développement backend, avec une solide pratique de Java ou Kotlin. Une première expérience avec Kafka, ou une forte envie de progresser sur le streaming et les systèmes distribués. Le souci de produire un code lisible, testé et maintenable. Une sensibilité aux enjeux de performance, de disponibilité et de fiabilité en production. Une première familiarité avec Docker, Kubernetes, la CI/CD ou l'observabilité. L'envie d'apprendre, de partager tes idées et de contribuer aux décisions techniques de l'équipe. Un anglais professionnel (B2) pour collaborer avec des équipes dans le monde entier. CE QUE NOUS T'OFFRONS Un impact concret et visible : ton travail compte dans les magasins Decathlon du monde entier. Une culture de la performance et de l'autonomie inspirée d'Accelerate : Kanban, livraison continue et amélioration continue de nos produits. Plus de 20 livraisons en production par semaine, avec un cycle time moyen de moins de 4 jours sur l'année. GitHub Copilot avec les derniers modèles d'IA, et Gemini, dans ton quotidien de dev. Un mode de travail hybride et flexible, avec des bureaux à Nantes. Du matériel au choix (Mac, Windows ou Chromebook). Des certifications techniques dès la première année, des conférences externes (DevFest…) et de grandes conférences tech internes, du temps dédié à la veille et une mobilité internationale possible. Une rémunération attractive, avec des bonus mensuels et trimestriels et l'actionnariat salarié. Tu ne coches pas toutes les cases ? Postule quand même, on en discute. DECATHLON DIGITAL Imaginez si la technologie nous permettait de repousser les frontières et d'offrir des expériences sportives inédites. C'est précisément notre ambition chez Decathlon Digital ! Nous sommes une équipe de plus de 5 000 experts en ingénierie logicielle, gestion de produits, données, cloud et cybersécurité, répartis à Paris, Lille et Amsterdam. Ensemble, nous créons la plus vaste plateforme sportive numérique, en exploitant les innovations technologiques pour optimiser la chaîne de valeur, concevoir des expériences connectées et donner une seconde vie à nos produits. Changeons la donne pour de bon. Notre passion du sport nous guide et nous voulons qu'elle perdure. C'est pourquoi nous nous engageons à bâtir un modèle technologique plus durable, en réduisant notre impact direct sur l'environnement, et en créant un espace sûr et inclusif pour apprendre et nous épanouir ensemble. Rejoins l'équipe et façonnons le futur du sport. Find Jobs in France on Arbeitnow

About Mirakl: Founded in 2012, Mirakl has been at the forefront of marketplace innovation, empowering every business to compete in the platform economy. Today, Mirakl's operating system combines an enterprise marketplace solution (Mirakl Platform) that enables retailers and B2B organizations to launch, scale, and operate marketplaces and dropship, AI-powered multichannel selling (Mirakl Connect), retail media (Mirakl Ads) and an agentic commerce infrastructure (Mirakl Nexus). With dual headquarters in Boston and Paris, Mirakl helps a global ecosystem of 450+ marketplaces (B2C and B2B) and a network of over 100k third-party marketplace sellers. Brands like Macy's, Decathlon, Carrefour, Asos, and Airbus Helicopters use Mirakl to grow their businesses in new and remarkable ways. For more information: www.mirakl.com . Mirakl in Numbers: 🗓️ Founded in 2012 | Member of French Tech Next40 👥 750+ employees in 9 offices worldwide: Paris, Barcelona, Bordeaux, Boston, London, Munich, New York, Sydney, Tokyo 🇫🇷 350+ Mirakl Tech teams members mainly based in France ⚙️ 5 Saas Solutions Our Values: Working at Mirakl means accelerating your career alongside ambitious, passionate, and supportive colleagues. We're proud of the diversity of backgrounds, perspectives, and experiences that make our teams unique. Our 5 values guide how we collaborate: 💡 Work Hard Together: Teamwork and collaboration are the foundation of our success 🏆 Get Things Done: We prioritize action and efficiency for impactful results 🚀 Go Above & Beyond: We tackle challenges proactively and always aim for excellence 🎓 Succeed Through Expertise: Knowledge sharing and continuous learning are core to our culture 🤝 Satisfy & Empower Clients: We're committed to our clients' success About the job Design, build, and scale production-grade AI systems that power the next generation of intelligent commerce. You will work at the intersection of Software Engineering, Machine Learning, and Generative AI to build AI-native products, agentic systems, and platform capabilities used by Mirakl customers and internal teams. This is a freelance position based in Paris or Bordeaux, with 1 day of remote work per week. Why Now, Why Mirakl Generative AI and AI Agents are fundamentally reshaping commerce software and the way our teams work on a day to day basis. At Mirakl, AI is becoming a core part of our product strategy. From Catalog Transformer and content generation to AI Agents and Agentic Commerce, we are building the next generation of commerce software. And we have the same ambition for our teams around AI products and adoption. We are looking for a Senior AI Engineer to transform the way our internal teams work, and to have a significant impact on the agentic side of our Saas products. You won't be joining a company that's thinking about AI. You'll be joining one that's already building it. What You'll Do 1. Design & Build AI Systems Design, build, and deploy production-grade AI systems for both Mirakl internal operations. Develop solutions leveraging: LLMs, RAG, AI Agents, Multimodal AI and Evaluation frameworks. Architect complex agentic workflows including tools, memory, retrieval, planning, and guardrails. Rapidly prototype new capabilities and evolve them into scalable, reliable AI production systems. 2. Integrate Across the Stack Connect AI systems to internal platforms, business applications, and data sources across the company. Enable AI agents to interact with systems such as CRM, data platform, Drive, Jira, support tools, and internal knowledge bases. Design robust orchestration layers between models, APIs, tools, retrieval systems, and business workflows. Ensure reliability, observability, scalability, and maintainability across the entire AI stack. 3. Iterate for Impact Partner with end users, business teams, Product Managers, and Engineers to identify high-value opportunities for AI. Run pilots and experiments, gather qualitative and quantitative feedback, and measure business impact. Analyze usage patterns, failure modes, costs, latency, and performance metrics. Continuously improve accuracy, reliability, adoption, and user experience through data-driven iteration. 4. Ensure Quality, Security & Reliability Implement evaluation frameworks, guardrails, validation layers, and monitoring systems. Design AI systems that are secure, explainable, and production-ready. Ensure compliance with data security, governance, and access control requirements. Document architectures, capabilities, limitations, KPIs, and operational best practices. 5. Drive Adoption & Enablement Build a scalable ecosystem of AI systems and agents that empower both internal teams and customers. Support teams in adopting AI-powered workflows and integrating AI into their daily operations. Contribute to AI engineering standards, reusable frameworks, and best practices across the company. Act as a champion for AI-driven ways of working and help shape Mirakl's transition toward Agentic Commerce. Our stack and tools Languages: Python and SQL AI Stack: OpenAI, Anthropic, Gemini, Mistral and Open-source models Agentic & Retrieval: LangGraph, LangChain, LlamaIndex, MCP and Vector Databases Infrastructure: AWS or GCP, Docker and Kubernetes What Makes You Successful Strong engineering mindset: able to design reliable and scalable systems Strong AI expertise: able to translate the latest AI capabilities into production products Strong product mindset: able to balance technical excellence with business impact Focus on measurable outcomes, not technical complexity Success Metrics Product adoption and business impact Performance and reliability of AI systems Quality of AI outputs and evaluation metrics You'll Love This Job If you have 5+ years of experience in Software Engineering, ML Engineering, Applied AI, or related fields Strong Python and software engineering fundamentals Hands-on experience building production AI systems using LLMs, RAG, and AI Agents Experience designing multi-step agentic workflows and retrieval systems Experience evaluating AI systems and improving model performance Experience deploying and operating production services in cloud environments Strong communication skills in English Curiosity, pragmatism, and passion for building AI products Feel free to add a link to your GitHub in your CV so we can understand what you have worked on! Want to join us? Here is our process A 30-40 min phone conversation with one of our Tech recruiters. This will be an opportunity to discuss your background, expectations, and discover what Mirakl can offer you in return. An initial 1h30 technical discussion with a member of the Data Science team and Engineering Team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects. 2 x 45-minute "STAR" interviews with future Mirakl colleagues to discuss our values and company culture. We welcome collaborators with their diverse perspectives and experiences to power us forward. These often far exceed conventional job requirements and help us create a culture of continuous learning. If you're ready to join a global leader powering digital transformation for 450+ of the world's most innovative retailers and B2B organizations. As part of our recruitment process, Mirakl processes your personal data to review and manage your application and, where appropriate, to consider your profile for future opportunities. You can exercise your data protection rights at any time, and as further detailed in our policies. For more information about how we process your personal data and your rights, please consult our Recruitment Privacy Notice, here in English and here in French. We may use Artificial Intelligence (AI) solutions to help streamline our hiring process, including screening applications, analyzing resumes, and assessing responses. While AI helps us work efficiently, all final hiring decisions are made by humans. For more information, visit our AI Guidelines for Candidates and Interviews . Find more English Speaking Jobs in France on Arbeitnow

About Mirakl: Founded in 2012, Mirakl has been at the forefront of marketplace innovation, empowering every business to compete in the platform economy. Today, Mirakl's operating system combines an enterprise marketplace solution (Mirakl Platform) that enables retailers and B2B organizations to launch, scale, and operate marketplaces and dropship, AI-powered multichannel selling (Mirakl Connect), retail media (Mirakl Ads) and an agentic commerce infrastructure (Mirakl Nexus). With dual headquarters in Boston and Paris, Mirakl helps a global ecosystem of 450+ marketplaces (B2C and B2B) and a network of over 100k third-party marketplace sellers. Brands like Macy's, Decathlon, Carrefour, Asos, and Airbus Helicopters use Mirakl to grow their businesses in new and remarkable ways. For more information: www.mirakl.com . Mirakl in Numbers: 🗓️ Founded in 2012 | Member of French Tech Next40 👥 750+ employees in 9 offices worldwide: Paris, Barcelona, Bordeaux, Boston, London, Munich, New York, Sydney, Tokyo 🇫🇷 350+ Mirakl Tech teams members mainly based in France ⚙️ 5 Saas Solutions Our Values: Working at Mirakl means accelerating your career alongside ambitious, passionate, and supportive colleagues. We're proud of the diversity of backgrounds, perspectives, and experiences that make our teams unique. Our 5 values guide how we collaborate: 💡 Work Hard Together: Teamwork and collaboration are the foundation of our success 🏆 Get Things Done: We prioritize action and efficiency for impactful results 🚀 Go Above & Beyond: We tackle challenges proactively and always aim for excellence 🎓 Succeed Through Expertise: Knowledge sharing and continuous learning are core to our culture 🤝 Satisfy & Empower Clients: We're committed to our clients' success About the job Design, build, and scale production-grade AI systems that power the next generation of intelligent commerce. You will work at the intersection of Software Engineering, Machine Learning, and Generative AI to build AI-native products, agentic systems, and platform capabilities used by Mirakl customers and internal teams. This is a freelance position based in Paris or Bordeaux, with 1 day of remote work per week. Why Now, Why Mirakl Generative AI and AI Agents are fundamentally reshaping commerce software and the way our teams work on a day to day basis. At Mirakl, AI is becoming a core part of our product strategy. From Catalog Transformer and content generation to AI Agents and Agentic Commerce, we are building the next generation of commerce software. And we have the same ambition for our teams around AI products and adoption. We are looking for a Senior AI Engineer to transform the way our internal teams work, and to have a significant impact on the agentic side of our Saas products. You won't be joining a company that's thinking about AI. You'll be joining one that's already building it. What You'll Do 1. Design & Build AI Systems Design, build, and deploy production-grade AI systems for both Mirakl internal operations. Develop solutions leveraging: LLMs, RAG, AI Agents, Multimodal AI and Evaluation frameworks. Architect complex agentic workflows including tools, memory, retrieval, planning, and guardrails. Rapidly prototype new capabilities and evolve them into scalable, reliable AI production systems. 2. Integrate Across the Stack Connect AI systems to internal platforms, business applications, and data sources across the company. Enable AI agents to interact with systems such as CRM, data platform, Drive, Jira, support tools, and internal knowledge bases. Design robust orchestration layers between models, APIs, tools, retrieval systems, and business workflows. Ensure reliability, observability, scalability, and maintainability across the entire AI stack. 3. Iterate for Impact Partner with end users, business teams, Product Managers, and Engineers to identify high-value opportunities for AI. Run pilots and experiments, gather qualitative and quantitative feedback, and measure business impact. Analyze usage patterns, failure modes, costs, latency, and performance metrics. Continuously improve accuracy, reliability, adoption, and user experience through data-driven iteration. 4. Ensure Quality, Security & Reliability Implement evaluation frameworks, guardrails, validation layers, and monitoring systems. Design AI systems that are secure, explainable, and production-ready. Ensure compliance with data security, governance, and access control requirements. Document architectures, capabilities, limitations, KPIs, and operational best practices. 5. Drive Adoption & Enablement Build a scalable ecosystem of AI systems and agents that empower both internal teams and customers. Support teams in adopting AI-powered workflows and integrating AI into their daily operations. Contribute to AI engineering standards, reusable frameworks, and best practices across the company. Act as a champion for AI-driven ways of working and help shape Mirakl's transition toward Agentic Commerce. Our stack and tools Languages: Python and SQL AI Stack: OpenAI, Anthropic, Gemini, Mistral and Open-source models Agentic & Retrieval: LangGraph, LangChain, LlamaIndex, MCP and Vector Databases Infrastructure: AWS or GCP, Docker and Kubernetes What Makes You Successful Strong engineering mindset: able to design reliable and scalable systems Strong AI expertise: able to translate the latest AI capabilities into production products Strong product mindset: able to balance technical excellence with business impact Focus on measurable outcomes, not technical complexity Success Metrics Product adoption and business impact Performance and reliability of AI systems Quality of AI outputs and evaluation metrics You'll Love This Job If you have 5+ years of experience in Software Engineering, ML Engineering, Applied AI, or related fields Strong Python and software engineering fundamentals Hands-on experience building production AI systems using LLMs, RAG, and AI Agents Experience designing multi-step agentic workflows and retrieval systems Experience evaluating AI systems and improving model performance Experience deploying and operating production services in cloud environments Strong communication skills in English Curiosity, pragmatism, and passion for building AI products Feel free to add a link to your GitHub in your CV so we can understand what you have worked on! Want to join us? Here is our process A 30-40 min phone conversation with one of our Tech recruiters. This will be an opportunity to discuss your background, expectations, and discover what Mirakl can offer you in return. An initial 1h30 technical discussion with a member of the Data Science team and Engineering Team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects. 2 x 45-minute "STAR" interviews with future Mirakl colleagues to discuss our values and company culture. We welcome collaborators with their diverse perspectives and experiences to power us forward. These often far exceed conventional job requirements and help us create a culture of continuous learning. If you're ready to join a global leader powering digital transformation for 450+ of the world's most innovative retailers and B2B organizations. As part of our recruitment process, Mirakl processes your personal data to review and manage your application and, where appropriate, to consider your profile for future opportunities. You can exercise your data protection rights at any time, and as further detailed in our policies. For more information about how we process your personal data and your rights, please consult our Recruitment Privacy Notice, here in English and here in French. We may use Artificial Intelligence (AI) solutions to help streamline our hiring process, including screening applications, analyzing resumes, and assessing responses. While AI helps us work efficiently, all final hiring decisions are made by humans. For more information, visit our AI Guidelines for Candidates and Interviews . Find Jobs in France on Arbeitnow

Centreon cherche à renforcer l'équipe sécurité en intégrant un senior security engineer. Au cœur du produit Centreon, la team security a un impact fort. Elle joue un rôle central au sein de la R&D composée d'environ 50 tech. Elle collabore notamment étroitement avec les équipes infra cloud et software engineers. Pluridisciplinaire, vous intégrez une équipe composée de 2 personnes au profils riches et variés. Vous êtes expert sur la partie Cloud et notamment AWS . Vous accompagnerez l'ensemble de la tech (dev, product, SRE) pour apporter les best practices, construire la plateforme, automatiser les process, déployer des composants, opérer des solutions etc Vos missions seront diverses et toujours guidées par l'envie de partager les succès mais avec un ownership fort. Missions : Intégrer les pratiques de sécurité dans le cycle complet de notre infrastructure et de notre plateforme cloud en interne ainsi que dans nos produits SaaS Contribuer au développement d'une architecture de sécurité robuste qui s'aligne sur le modèle zéro trust Renforcer la sécurité du cloud (AWS, on-prem), participer au hardening de l'infra, à la protection contre les menaces avancées et à la conception de SaaS sécurisés Participer activement à une équipe d'ingénieurs diversifiée composée d'ingénieurs en sécurité, d'ingénieurs logiciels, de devops et de SRE Construire et opérer la stratégie de sécurisation des usages et technologies d'IA au sein de l'entreprise Garantir la maintenabilité et l'évolutivité des différents composants, en diffusant les best practices de sécurité à l'état de l'art Collaborer avec les software engineers, l'équipe infra et le produit pour construire des produits et des services secure by design Construire une stratégie de réponse aux incidents efficace et solide à l'aide de systèmes d'alerting et de détection modernes Corriger et mitiger les problèmes de sécurité en collaboration avec l'équipe Infra Faire évoluer les capacités de l'équipe sécurité en s'appuyant sur l'IA agentique pour automatiser le traitement des tâches répétitives (alertes, triage, reporting) Être un membre actif de la guilde de sécurité Bug Bounty management Stack technique : AWS – Terraform – Zero trust : Okta, Teleport - SSLDC - SIEM Profil et compétences Vous êtes autonome et faites preuve d'ownership, êtes capable de leader des projet transverses Vous avez une expérience significative en sécurité des infra cloud : système, réseau et notamment AWS Vous avez une bonne compréhension de la sécurité dans les systèmes distribués à l'échelle. Vous avez une bonne connaissance de la gestion de l'IAM sur les fournisseurs de cloud (AWS, Auth0) Vous maîtrisez un ou plusieurs langages de notre stack tech Vous avez un intérêt pour l'écosystème OpenSource et pour le monitoring Vous aimez innover et faire évoluer les architectures des plateformes vers une plus grande scalabilité Vous voulez être un membre actif d'une équipe d'ingénieurs diversifiée composée d'ingénieurs en sécurité, d'ingénieurs logiciels, de devops et de SRE Les plus qui feront la différence : Vous avez des compétences ou expériences et intérêt pour la sécurité corporate IT (SSO/IAM, EDR, MDM...) Vous êtes sensible à la culture de l'open-source Vous êtes sensible à l'expérience utilisateur (performance, ergonomie, utilisabilité, etc.) Vous aimez défier vos collègues au babyfoot ! Ce que nous offrons Société en forte croissance (+20% en 2025) dans un environnement international Venez apprécier nos locaux à Paris avec terrasse à Olympiade - Métro ligne 14 ou à Toulouse quartier Compans Caffarelli (immeubles accessibles PMR) RTT et Carte Tickets restaurant Events mensuels et semestriels Petits dej mensuels Un programme d'Onboarding Pleins d'autres avantages --> https://centreon.recruitee.com/qui-sommes-nous Nous avons à cœur de mettre en avant la diversité au sein de notre entreprise. Tous les candidats qualifiés seront pris en considération pour un emploi sans distinction de race, de couleur, de religion, de sexe, d'orientation sexuelle, d'identité de genre, de nationalité ou de toute autre caractéristique protégée par la loi dans le pays où le candidat postule. Ce poste est ouvert aux personnes en situation de handicap. Find Jobs in France on Arbeitnow

Set a new pulse for healthcare! We are looking for a Senior Agents Platform Engineer to join the ML Platform (TIGER) team in AI & Machine Learning . Your mission will be to build the platform that lets every feature team at Doctolib declare an agent once — and get a production-grade, secure, and compliant AI agent by default. You will work on the foundational layer that powers Consultation Assistant, Phone Assistant, Health Companion, and more: a shared agent runtime, a unified GenAI gateway, and the observability and evaluation infrastructure that makes it all trustworthy — contributing directly to safer, faster, and more reliable AI for patients and care teams across Europe. Working in the tech team at Doctolib means building innovative products and features to improve the daily lives of care teams and patients. What you'll do Your responsibilities include but are not limited to: Own the agent manifest and registry — design the single declarative specification (skills, tools, memory, model, guardrails, sandbox, security) that wires any new agent into the full platform automatically, triggerable from product surfaces, other agents (A2A), schedules, or workflows Own the GenAI gateway end to end (built on LiteLLM) — manage routing (including KV-cache-aware routing), failover, metering, cost attribution, reserved-capacity pooling, and guardrails across self-hosted (vLLM) and managed providers, serving several hundred million requests per month Operate the infrastructure for long-running, streaming agent interactions — build production-grade reliability for SSE/WebSocket connections, queueing and retries, human-in-the-loop approvals, and snapshot/resume, in a sandboxed execution environment consistent with our existing application runtime Build feature-flagged, progressive rollout for prompts, models, and configs — including an emergency kill-switch and the audit trail that lets agents act safely on sensitive healthcare data Own reliability for the agents platform end to end — define SLOs, lead on-call and incident response, and build runbooks including provider failover for the GenAI gateway Build the observability and evaluation layer — online traces and logs, offline evals (LLM-as-judge plus patient and practitioner simulators) gating CI, and the compliance-grade audit trail for health data Validate the platform by shipping one or two reference agents yourself before product teams adopt it, and advise feature teams on agent architecture trade-offs Who you are Before you read on: if you don't have the exact profile described below, but you feel this job description matches your skill set, we still encourage you to apply. You'll be a great fit if you: Have 5+ years of software engineering experience, including hands-on production experience building or operating LLM-based agent systems (Google ADK or similar), with a solid understanding of agent design patterns: planning/reflection loops, tool calling, state and memory management, multi-agent coordination, and human-in-the-loop checkpoints Have experience with agent interoperability and tool protocols (MCP, A2A, AG-UI), control-plane concepts for asynchronous or long-running systems (queueing, retries, checkpointing), and feature-flagging or progressive-rollout systems including reliable kill-switches Have experience managing cost and capacity for LLM usage — routing, caching, and reserved-capacity planning with managed model providers Are comfortable owning production reliability (SLOs, incident response, on-call) and are security-minded when designing sandboxing, permission scoping, and audit trails for autonomous systems acting on sensitive data Have excellent communication and collaboration skills, high agency, a pragmatic build-vs-buy mindset, and are comfortable working in a founding role where shaping the right scope is part of the job Are fluent in English It would be fantastic if you: Have experience giving agents richer identity, memory, and knowledge (long-term memory, artifact stores, or RAG pipelines), ideally in partnership with a data platform team, or experience building a feedback loop that turns production traces into evaluation datasets Have experience building Kubernetes-native abstractions (CRDs/operators) to manage an agent's lifecycle declaratively, and/or with durable stateful execution engines (e.g. Temporal) for long-running workflows Have experience in regulated environments (healthcare, finance, public sector) and with frameworks such as GDPR, HDS, ISO 27001, or SOC 2 Our stack Programming languages: Python, plus comfort with TypeScript/Go for agent SDKs and tool integrations Cloud providers: GCP / AWS / Azure Agent orchestration & runtime: Google's Agent Development Kit (ADK), running as services on our application platform Agent protocols: MCP, A2A, and AG-UI Feature flags / progressive rollout: Flagd (or similar), including the emergency kill-switch GenAI gateway: LiteLLM (owned end-to-end by this team) — routing, failover, metering, cost attribution, guardrails, reserved-capacity pooling (Azure OpenAI PTUs, Vertex AI GSUs, AWS Bedrock Provisioned Throughput) Experiment tracking & model registry: MLflow LLM evaluation & observability: Braintrust and Datadog LLM Observability, plus distributed tracing for tool calls and agent decision paths Container / Orchestration: Kubernetes (GKE / EKS), Docker, Helm, Kustomize Infrastructure as code: Terraform Observability: Datadog And any other tool you deem relevant! Life at Doctolib Tech Our solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to country and healthcare specialty requirements. Our stack is composed of Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native. We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here . Want to learn more about our tech culture and environment? Visit the Doctolib Tech site . What we offer Free comprehensive health insurance (basic package) for you and your children 25 days of paid vacation per year, plus up to 14 days of RTT Free mental health and coaching services through our partner Moka.care Work from abroad for up to 10 days per year thanks to our flexibility days policy Lunch vouchers (Swile card) worth €8.50 per working day, with €4.50 covered by Doctolib A subsidy from the work council to refund part of the membership to a sport club or a creative class 50% reimbursement of your public transport subscription ParentCare Program: Enjoy full salary coverage (100%) during your first month of birth leave and 75% during the second, covered by Doctolib Enrollment in Doctolib's long-term employee value sharing plan called DoctoGrowth For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support Relocation support in case of international mobility Access to the best AI tools for coding, development and dedicated training Our interview process HR interview by phone (45 minutes) Hiring manager interview (1 hour) Case study & case restitution (1 hour) Behavioral interview (1 hour 30 minutes) At least one reference check We want your experience to be clear, respectful, and transparent. Learn more about our hiring process on our candidate experience page . Job details Permanent position Tech stack: Python, LiteLLM, Google ADK, Kubernetes Full-time Paris, France Hybrid work setup (up to 2 remote days per week) Start date: as soon as possible We welcome everyone At Doctolib, we are committed to improving access to healthcare for everyone. This translates into our recruitment process. We evaluate candidates based solely on qualifications and motivation, without any form of discrimination. The more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, or disability. To ensure equal opportunities, we invite you to exclude personal information (e.g., pictures, age) from your applications. If you require any accommodation, please let us know for support during the hiring process. Join us in building the healthcare we all dream of! Your data privacy All information provided is processed by Doctolib for application management. For data processing details, click here: France . Please contact hr.dataprivacy(at)doctolib.com for inquiries or to exercise your rights. Find more English Speaking Jobs in France on Arbeitnow

Your Impact at LILA We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to identify and mitigate risks from scientific superintelligence while retaining the core scientific discovery capabilities of the stack. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, safety-focused evaluations, safety systems to mitigate risks, and a research agenda that explores longer-term needs such as oversight of superintelligent scientific systems. At Lila's AI Safety team, you will build the shared software that helps our team understand and reduce societal risks from scientific AI. Working with researchers, domain scientists and program colleagues, you will turn needs across threat modeling, evaluations, red teaming and mitigation development into reliable tools and systems. You will own engineering work from scoping and prototyping through deployment and ongoing improvement, supporting research across scientific models, agents and automated experimentation. What You'll Be Building Build reusable services, libraries and model/tool integrations that make evaluations, red-teaming campaigns and mitigation experiments repeatable. Develop applications that help researchers and scientific experts organize evidence, inspect results, review data and investigate failures. Work with safety colleagues to understand research needs and identify shared engineering needs, prioritize useful improvements and turn evolving research workflows into maintainable software. Build data pipelines and experiment records that preserve datasets, taxonomies, model versions, configurations and results, making findings traceable and comparisons reproducible. Own the reliability and usability of shared safety tools through testing, debugging, monitoring, documentation and continued improvement. Collaborate across LILA with our core AI and software engineering teams to share tooling, align on infrastructure, and avoid duplication. What You'll Need to Succeed A track record of independently delivering and maintaining production software, including projects with ambiguous or changing requirements. Strong Python and backend engineering skills, with experience designing APIs, working with databases and building dependable data or execution pipelines. Experience translating the needs of researchers, domain experts or other technical users into usable tools, and comfort working across services and interfaces. Sound engineering judgment in system design, testing and debugging, including practical decisions about reliability, performance and complexity. Engineering experience in AI research, AI safety, scientific computing or other settings with rapidly evolving experimental workflows. Clear communication and an interest in scientific AI safety, with the ability to understand research context and make informed engineering decisions. Bonus Points For Building safety-specific tooling. Building full-stack internal applications, annotation or review tools, or systems for managing experimental evidence. Experience with distributed experiment execution, model-serving integrations or isolated environments for agent evaluations. Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $192,000 — $272,000 USD About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. We're All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto. Find Jobs in United Kingdom on Arbeitnow

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,500 firms in 60 countries use Addepar to manage and advise on nearly $10 trillion in assets. Its open platform integrates with 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and levels of complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, São Paulo, London, Edinburgh, Geneva, Warsaw, Dubai, Pune and Singapore. The Role We are currently seeking a Staff Software Engineer with AI/ML background to join our Reference Data team. The reference data team at Addepar is responsible to manage the data reconciliation and curation process for market data providers to build a single source of truth and provide alignment across public and alternative investment data products for the client to manage their investment portfolio. As an engineer on the team you will partner with product teams at Addepar to understand their business needs. The team is focused on enabling and building disruptive, innovative solutions to transform the wealth technology landscape with AI across our product suite and is growing quickly. You will be responsible for architecting, leading, and driving the execution of the core AI capabilities that power our platform. This is a high-impact role for an engineer who thrives on the frontier of applied AI and maintains a relentless focus on shipping. You will not just work with LLMs and agentic frameworks; you will own the end-to-end delivery of AI-native products, ensuring that cutting-edge AI systems are hardened into robust, scalable, and high-performance production systems. Applicants must have, and maintain, the right to work in the United Kingdom from the first day of employment. Please note that visa sponsorship is not available for this role. What You'll Do Drive the end-to-end execution and delivery of AI-native products, moving from initial prototype to scalable production services with high velocity Architect, build, and productionize core components of our AI platform – including: LLMs and the surrounding ecosystem (e.g., vector DBs, prompt tuning, etc.) Agentic frameworks Core agent capabilities like MCP/ cross-platform tool use, web browsing, computer use Enforce technical discipline and operational excellence for all of our AI products Rapidly iterate on AI products based on performance metrics and user feedback to drive continuous improvement Lead the evaluation and adoption of new AI technologies and frameworks to keep Addepar on the frontier of the industry Partner with product managers and other engineering teams to translate strategic goals into technical realities, abstracting AI complexity so they can iterate quickly Collaborate closely with our engineering leads to define and implement our platform architecture to meet Addepar's growth and scalability needs Evaluate and drive strategic business and technology decisions for the company and for customers Be a technical thought leader in multiple areas who educates and shares best practices. Your contributions deliver strategic and prescriptive guidance Who You Are B.S., or M.S. in Computer Science or similar technical field of study (or equivalent practical experience) Extensive software engineering experience Proven track record of owning and shipping complex, production-grade systems. Proven experience shipping and maintaining AI-native products or features, or demonstrable passion through significant personal projects in AI Deep ownership mindset, seeing projects through to completion and raising the bar for execution across the team A strong bias for action, with a passion for shipping rapidly and iterating with feedback BS/MS in Computer Science, Statistics, Mathematics, or another quantitative field, or equivalent experience [Preferred] Specific experience with LLMs and agentic systems [Preferred] Hands-on experience with technologies in the modern AI/LLM ecosystem, such as Databricks, Langchain, or MLFlow [Preferred] Advanced understanding of the probabilistic systems underpinning modern LLMs [Preferred] Experience building AI products in highly accuracy-sensitive domains such as finance is a plus Our Values Act Like an Owner - Think and operate with intention, purpose and care. Own outcomes. Build Together - Collaborate to unlock the best solutions. Deliver lasting value. Champion Our Clients - Exceed client expectations. Our clients' success is our success. Drive Innovation - Be bold and unconstrained in problem solving. Transform the industry. Embrace Learning - Engage our community to broaden our perspective. Bring a growth mindset. In addition to our core values, Addepar is proud to be an equal opportunity employer. We seek to bring together diverse ideas, experiences, skill sets, perspectives, backgrounds and identities to drive innovative solutions. We commit to promoting a welcoming environment where inclusion and belonging are held as a shared responsibility. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. PHISHING SCAM WARNING: Addepar is among several companies recently made aware of a phishing scam involving con artists posing as hiring managers recruiting via email, text and social media. The imposters are creating misleading email accounts, conducting remote "interviews," and making fake job offers in order to collect personal and financial information from unsuspecting individuals. Please be aware that no job offers will be made from Addepar without a formal interview process. Additionally, Addepar will not ask you to purchase equipment or supplies as part of your onboarding process. If you have any questions, please reach out to <a ---------- Find Jobs in United Kingdom on Arbeitnow