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Job Number: R0252233 Artificial Intelligence Engineer The Opportunity: As an AI Engineer, you will bring advanced AI capabilities into production systems by integrating models, inference endpoints, agent‑orchestration frameworks, and intelligent workflows into complex, distributed software environments. You will apply strong software engineering principles to ensure these AI features operate reliably, securely, and efficiently at scale. In this role, you will help evolve traditional LLM-driven solutions into goal‑oriented, multi‑agent architectures leveraging agent‑orchestration frameworks, Retrieval-Augmented Generation (RAG), Knowledge Graphs (KGs), and fine‑tuned Small Language Models (SLMs). You will contribute to evaluation and monitoring strategies, refine integration workflows, collaborate with cross‑functional engineering teams, and develop scalable AI capabilities that translate cutting‑edge concepts into operational, mission‑ready solutions. Join us. The world can't wait. You Have: 3+ years of experience developing and maintaining production-grade software systems in Python Experience designing and implementing AI agent architectures using LangChain, LangGraph, AutoGen, MCP, or A2A Experience building RAG solutions with Knowledge Graphs and fine‑tuning SLMs using ONNX, GGML, or Ollama Experience integrating LLMs, external APIs, and distributed services into production with optimized inference workflows Experience developing AI evaluation frameworks, integration tests, and production validation using ReAct patterns and human‑in‑the‑loop methodologies Knowledge of secure HTTP APIs, OAuth2, JWT, API Keys, containerization, and CI/CD pipelines Ability to travel up to 25% of the time TS/SCI clearance Bachelor's degree in Computer Science, Engineering, or Data Science DoD 8140 Level II Certification such as Security+, CySA+, or CISSP Certification Nice If You Have: Experience supporting DoD clients or other federal mission environments Experience with advanced agentic patterns, including prompt caching, guardrails, agent memory, Model Context Protocol (MCP), and agent deployment strategies Experience developing end‑to‑end chatbot or agent‑to‑agent (A2A) systems Experience with enterprise data and machine learning platforms such as Databricks or Snowflake Experience building or managing large‑scale data processing pipelines Master's degree in a related field Clearance: Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance is required. Compensation At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen's benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page. Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen's total compensation package for employees. This posting will close within 90 days from the Posting Date. Identity Statement As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud. Candidate AI Usage Policy AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided . Work Model Our people-first culture prioritizes the benefits of collaboration. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings. Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility. Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen or customer facility, in alignment with your leadership's expectations and the needs of the role. Onsite: If this position is listed as onsite, work will primarily be performed full-time at a customer facility, where employees will collaborate directly with colleagues and customers as required by the role. Commitment to Non-Discrimination All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.

Language Model Scientist We're hiring a Language Model Scientist in Santa Clara, California, to join L&T's AI Center of Excellence. You'll build the generative and agentic AI systems that power knowledge, engineering and operations across the L&T Group, turning foundation-model capabilities into secure, reliable and domain-aware solutions: copilots, AI agents, enterprise knowledge systems and natural-language interfaces to engineering and physical systems. What you'll do Fine-tune and align open-source and commercial LLMs (SFT, LoRA/PEFT, RLHF, DPO) for domain tasks such as engineering specifications, contracts, standards and code. Design agentic systems with tool use, planning, memory and multi-agent orchestration, plus RAG and knowledge-graph systems over enterprise data. Build evaluation, guardrail and red-teaming frameworks covering accuracy, hallucination, bias and safety. Deploy and scale LLMs in production (vLLM, TensorRT-LLM, quantization), with monitoring and inference cost optimization across cloud and on-premise. Partner with businesses in Engineering, Manufacturing, Infrastructure, Energy, Financial Services, IT Services and Defence to deliver high-value GenAI use cases. First 12 months Enterprise LLM and agentic AI reference architecture defined for the CoE. 5–8 GenAI and agentic use cases delivered, at least 3 scaled to production. At least one domain-adapted language model developed. LLM evaluation, guardrail and LLMOps framework established. What we're looking for Master's or PhD in Computer Science, AI, NLP, Computational Linguistics or a related field (PhD preferred). 8–15 years in ML or NLP, including 3+ years of hands-on work with LLMs and Generative AI. A track record of building and deploying LLM applications in production at enterprise scale. Deep knowledge of transformer architectures, pre-training, fine-tuning and alignment. Strong Python with PyTorch, Hugging Face, DeepSpeed/FSDP and LLM frameworks such as LangChain, LlamaIndex or LangGraph. Experience with vector databases, knowledge graphs, Model Context Protocol (MCP) and function calling. Plus: engineering, industrial or regulated-domain experience, and publications at ACL, EMNLP, NAACL, NeurIPS, ICML or ICLR. Role details: Reports to the Head, AI Center of Excellence. Headcount: 3. Scope: L&T Group-wide, United States and India. Interested? Apply or send us a message with your profile. #LTGroup #AI #LLM #GenerativeAI #AgenticAI #Hiring #SantaClara

Machine Learning EngineerAbout Blue Voice At Blue Voice our primary mission is to empower first responders with state-of-the-art SaaS solutions, leveraging machine learning and LLMs. We seek to modernize and revolutionize their workflow, response times, and overall efficiency while improving outcomes in the field. We are a venture-backed startup with a lean team distributed across the country and pods on the East and West coasts. The Role Position: Machine Learning Engineer Reports to: Director of ML Location: Remote (US). SF Bay Area preferred, with opportunities for in-person work. Key Responsibilities: Collaborate closely with the Director of ML and the rest of the founding engineering team to design, implement, and iterate on our core SaaS product. Contribute to the full ML lifecycle for products, from design and implementation to evaluation and training, as well as to backend and occasional full-stack initiatives outside the traditional ML scope. Monitor production quality, surface regressions proactively, and help harden existing systems. Triage customer-reported issues end-to-end, identifying root causes and turning them into fixes and eval cases. Keep up to date with the latest developments in ML, specifically in LLMs and RAG, and be comfortable discussing new tools and approaches. Actively participate in product decisions and project deliverables, collaborating across the company with customer success and sales. Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or a related field. 3-4 years of software engineering experience. We weigh what you've built and shipped alongside years of experience and welcome earlier-career applicants with strong work to show. Proficiency in Python and familiarity with modern software development best practices, including integrating AI into the development life cycle. Strong ML fundamentals, specifically LLMs and related technologies. Experience developing and deploying customer-facing SaaS applications. Solid backend fundamentals: APIs, data pipelines, testing, and debugging across service boundaries. Knowledge of or willingness to learn mobile application deployment and integration of ML components with mobile full stack development on React Native. Eligible for CJIS access: you must be a US person able to pass a fingerprint-based background check. Preferred Qualifications: Experience with cloud platforms (e.g., AWS, Azure, GCP) and deploying scalable ML solutions in the cloud. Experience with CI/CD pipelines and Agile methodologies. Prior exposure to, or a strong interest in, the first responder ecosystem or related fields. You'd be a great fit for this role if you: Are a self-starter with the ability to learn new skills quickly and pivot in a fast-evolving environment where development and deployments happen in a matter of days. Bring an opinion. When you find something, say what should change and why. Have a genuine passion for technology, in particular LLMs, and their potential to positively impact society. Benefits: Competitive salary and equity. Opportunities for professional growth and leadership in a fast-growing startup. Flexible working hours and fully remote work. Health and wellness benefits. For more information or to apply, please send your resume accompanied by a brief introduction and any relevant portfolio or project links to amit@bluevoice.io and CC jordan@bluevoice.io Blue Voice is an equal opportunity employer. We are committed to building a diverse and inclusive team and encourage applications from candidates of all backgrounds and experiences.

About Us Think BIG. Achieve More. At City National Bank of Florida, we invest in our people and the communities we serve. Join a team where ambitious careers and meaningful relationships thrive together. We're entrepreneurs at heart—growing fast, making an impact, and shaping the future of banking in Florida. To learn more about City National Bank of Florida visit About Us! Overview City National Bank of Florida is seeking a hands-on Machine Learning / AI Engineer to develop enterprise-grade AI applications, retrieval-augmented generation (RAG) systems, and agentic AI workflows. The engineer will work on real banking use cases involving financial document analysis, credit writing, enterprise knowledge retrieval, risk and fraud prevention, and employee productivity. The ideal candidate combines strong Python software engineering skills with practical experience building, testing, and deploying LLM-powered applications. This is a development-focused role, not a pure research or experimentation position. What You'll Do Design, develop, test, and maintain production-quality Python applications for generative AI and applied machine learning. Build RAG pipelines using document ingestion, parsing, chunking, embeddings, metadata filtering, hybrid search, reranking, and grounded response generation. Develop AI agents and workflow components using LangChain v1 and LangGraph. Integrate Azure OpenAI models and Azure AI Search into enterprise AI applications. Implement structured outputs using Pydantic, schema validation, deterministic business rules, and robust error handling. Build document validation, financial data extraction, summarization, classification, and analysis components. Implement automated evaluation datasets and tests to measure retrieval quality, answer correctness, grounding, and regression. Develop REST APIs and backend services using FastAPI or an equivalent Python framework. Write unit tests, integration tests, and mock-based tests; participate in code reviews and continuous integration. Implement secure handling of sensitive banking information, prompt-injection defenses, input validation, and appropriate AI guardrails. Deploy containerized applications and contribute to Azure monitoring, logging, troubleshooting, and performance optimization. Collaborate with senior engineers, AI leadership, business stakeholders, and risk and compliance teams. Qualifications Programming and software engineering 4–5 years of professional software development experience, with strong hands-on Python proficiency. Strong knowledge of object-oriented programming, data structures, algorithms, modular design, and clean-code principles. Experience with FastAPI, REST APIs, Pydantic, SQL, Git, pytest, and debugging. Generative AI and machine learning Practical experience building LLM-powered applications using OpenAI, Azure OpenAI, or comparable model APIs. Understanding of transformers, embeddings, tokenization, semantic search, and model inference. Hands-on experience with RAG, including document ingestion, chunking strategies, retrieval, grounding, and evaluation. Experience with LangChain, LangGraph, or comparable orchestration frameworks. Direct LangGraph experience is strongly preferred. Experience with prompt design, structured generation, function/tool calling, and output validation. Ability to measure and improve AI quality rather than relying solely on subjective demonstrations. Cloud and engineering practices Experience with Azure or another major cloud platform; Azure experience is preferred. Familiarity with Docker, CI/CD, application logging, monitoring, and automated testing. Ability to troubleshoot API failures, retrieval defects, latency, token usage, and model-related errors. Preferred Qualifications Experience with Azure AI Search, hybrid search, reranking, or vector databases. Experience building AI agents that call enterprise APIs and tools. Familiarity with Model Context Protocol (MCP). Experience with PostgreSQL, Azure Blob Storage, or document-processing pipelines. Experience in banking, financial services, lending, fraud, or another regulated industry. Familiarity with responsible AI, data privacy, and auditability. Education Bachelor's Degree in computer science, data science, engineering, applied mathematics/statistics, information systems, or a related quantitative field (or equivalent combination of education and experience). Master's Degree preferred. Benefits & Perks We offer a competitive benefits package designed to support your success: Health Coverage: Medical, dental, and vision plans with employer contributions. Retirement Savings: 401(k) with matching. Paid Time Off & Holidays: Generous PTO and paid holidays. Wellness Support: Access to mental health and financial wellness resources. Visit our benefits page to learn more Benefits! Join City National Bank of Florida. The possibilities are endless. Special Information To Candidates Equal Opportunity City National Bank of Florida is an Equal Opportunity Employer. We do not discriminate based on race, color, religion, sex, national origin, age, disability, genetic information, protected veteran status, or any status protected by federal, state, or Florida law. We comply with the ADA and applicable Florida laws. Interview Guidelines To ensure a fair and consistent interview process, applicants are not permitted to use AI-enabled devices during interviews, including AI glasses or similar wearable technology that can record, transmit, or generate real-time information. Applicants who require a reasonable accommodation to participate in the interview process should contact talent.attraction@citynational.com in advance of the interview to submit an accommodation request. City National Bank of Florida will engage in the interactive process and provide reasonable accommodations in accordance with applicable law.

See yourself at Dataminr As a Senior AI Engineer at Dataminr, you'll work alongside Research Scientists and Data Scientists to train, adapt, and deploy state-of-the-art LLMs and agents across Predictive, Generative, and Agentic AI. You'll tackle multimodal data, including text, images, video, audio, and sensor data, on a platform that processes billions of inputs every day, helping organizations act on critical events as they unfold. Expect plenty of room to keep growing in both AI and software engineering. This is a hybrid role with two in-office days each week in our New York City or Arlington, VA office. AI Innovation at Dataminr Working at Dataminr you'll have the opportunity to tackle the most exciting trends in AI on a daily basis to power a revolutionary product that uncovers critical events around the world as they unfold. Regenerative AI: our AI technology, ReGenAI, is a new form of generative AI that automatically regenerates real-time Live Event Briefs as events unfold. Learn more here. Agentic AI: we recently launched our Agentic AI capability, what we're calling our Intel Agents, that autonomously generates critical context for our clients on real-time events, threats, and risks allowing them to see the clearest, most accurate view of what's happening on the ground. Learn more here Multimodal AI: our platform detects events from many different types of data (images, video, sensor data, audio, and text in over 150 languages). Learn more here. The opportunity Work with groups of Research Scientists, Engineers, and Data Scientists in the AI Platform organization and beyond, to deploy, build, adapt, optimize, and deploy LLM models in production at very large scale. Own the technical design and implementation of robust API services, libraries, and container strategies that define and support our end-to-end LLMOps lifecycle. Optimize DL/LLM training and inference performance (speed/cost) on specialized hardware. Drive the full lifecycle of complex AI problems: from initial research and literature review to hands-on data exploration, implementation of novel, in-house methods, and successful productization. What You Bring At Dataminr, we value you for who you are. We encourage you to apply for this role, even if you don't meet every qualification. Our candidates are reviewed on the basis of their skill and potential to succeed. M.S. in Computer science or equivalent experience 5+ years of experience as a Research or Machine Learning Engineer. MLOps/LLMOps Experience: building, optimizing, deploying and operating Deep Learning models using PyTorch, including Transformers and LLMs, not just using APIs. Experience working with Research Scientists, reading technical research papers, and implementing state-of-the-art methods in Natural Language Processing, Computer Vision, Knowledge Representation and Management, Vector Databases and Generative AI. Expertise in Python. Experience with Containers, Kubernetes, AWS, Databricks, and Agentic infra such as LangGraph, LangFuse, and vector stores About Dataminr At Dataminr, we are a mission driven team of talented builders, creators and visionaries who have real-world impact on how organizations are able to respond to events. Dataminr's groundbreaking, AI-powered, intelligence platform provides organizations with the earliest signals of emerging risks, events, and threats before they unfold. Trusted by two-thirds of the Fortune 50 and half of the Fortune 100, Dataminr's platform analyzes billions of public data inputs spanning text, image, video, audio and sensor data across 150+ languages, empowering our clients to stay one step ahead in an increasingly complex world where every second counts. Founded in 2009, we have pioneered the world's first real-time event detection platform, long before the recent Gen AI 'boom.' Dataminr operates all around the world united by our passion to use AI for the greater good, be agents of positive change and put our technology into the hands of clients charged with the responsibility to keep organizations running and keep people safe. As our employees focus on developing our revolutionary technology, we focus on our employees. Dataminr is proud to offer a variety of flexible work arrangements, offices all over the world to foster collaboration, generous PTO and sick leave, and more, as part of our competitive benefits package aimed at keeping all our employees happy and healthy. Explore all our benefits here . We believe our differences give us strength. Our employees are empowered to be their best, authentic selves through various opportunities, such as our robust employee resource group (ERG) network, manager development programming, professional development funds, and more. We serve a global community made up of many cultures and strive to reflect the world and clients we serve, with a workforce built on merit and equity. We actively condemn racism and discrimination in any form. We stand for social good, fostering a culture of allyship, and standing up for those who face systemic barriers to equality. We lead with empathy and strive to be agents of positive change in our company and in our communities. The annual base salary range for this position is $154,800 - $227,500. You will also be eligible to receive a discretionary bonus and Company equity. Actual salary will be based on a number of factors including, but not limited to, geographic location, applicant skills, and prior relevant experience. Dataminr is an equal opportunity and affirmative action employer. Individuals seeking employment at Dataminr are considered without regards to race, sex, color, creed, religion, national origin, age, disability, genetics, marital status, pregnancy, unemployment status, sexual orientation, citizenship status or veteran status. Dataminr will collect and process your personal data in accordance with Dataminr's candidate privacy notice available here . By providing your details and applying via our careers website, you acknowledge that you have read our candidate privacy notice. If you have any queries, please contact recruiting@dataminr.com or privacy@dataminr.com . Notice Regarding Automated Employment Decision Tools in New York City

About The Role The role designs and ships production LLM and GenAI systems: retrieval-augmented generation pipelines, agentic workflows, fine-tuning jobs, and evaluation harnesses that hold up under real enterprise traffic. This is not a prompt-tinkering position. The team builds the core AI platform — model serving infrastructure, evaluation frameworks, and RAG architecture — and this role owns meaningful pieces of it end-to-end, working alongside applied scientists, backend engineers, and product leadership. Key Responsibilities Architect and build RAG pipelines using LangChain, LlamaIndex, or custom retrieval stacks, tuning chunking strategies, hybrid search, and reranking for measurable quality gains Implement and scale vector database integrations (Pinecone, Weaviate, pgvector) serving low-latency semantic search in production Design agentic workflows with tool calling, function execution, and guardrails using frameworks like LangGraph or custom orchestration layers Run fine-tuning workloads (LoRA, QLoRA, DPO) on domain-specific datasets using PyTorch and Hugging Face, managing GPU resources across training runs Build systematic LLM evaluation frameworks: golden datasets, LLM-as-judge pipelines, and regression suites wired into CI so quality regressions are caught before deploy Deploy and serve models via vLLM, Triton, or managed inference endpoints, optimizing for cost, latency, and throughput Own observability for GenAI features: tracing with LangSmith or OpenTelemetry, drift detection, and dashboards that surface failure modes quickly What We Are Looking For 3–6 years of software engineering or ML engineering experience, with at least 2 years shipping LLM-powered systems to production Strong Python engineering skills: async programming, API design, testing, and working comfortably in large codebases Hands-on production experience with RAG architecture, including embedding model selection, vector databases, and retrieval quality tuning Experience fine-tuning or evaluating open-source models (Llama, Mistral, Qwen) and working with provider APIs (OpenAI, Anthropic, Bedrock) Working knowledge of cloud infrastructure (AWS, GCP, or Azure), containerized deployments, and GPU-based serving Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience Bonus: experience with RLHF or preference optimization, contributions to open-source LLM tooling, multimodal model experience, or an MS/PhD in a relevant field

Scribd, Inc. is on a mission to advance human understanding. Our four products — Scribd®, Slideshare®, Everand™, and Fable — help billions of people across the globe move beyond access and into insight, application, and expertise. Culture at Scribd, Inc. We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. We believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in-person moments that strengthen collaboration and culture. Occasional in-person attendance is required for all Scribd, Inc. employees, regardless of location. So what are we looking for in new team members? At Scribd, Inc., we hire for "GRIT." Traditionally defined as the intersection of passion and perseverance toward long-term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude. This posting reflects an approved, open position within the organization. About The Team Premium is the Scribd Inc. pillar behind two reading products: Everand, the audiobook and ebook subscription app, and Fable, the social app where readers track, discuss and discover books. Helping readers find their next book is central to both, so search and recommendations sit at the heart of the products. You'll join Premium's new Discovery squad. It's a small, dedicated group of recommendations, search, applied research and ML engineers working full time on discovery for Everand and Fable. The squad works closely with Orion, Scribd's ML platform team. Orion runs the feature store, model registry, embedding-based retrieval and model serving behind discovery across Scribd, Slideshare and Everand. Role Overview We're looking for a Senior Machine Learning Engineer to own recommendations for Fable and grow into the technical lead for Premium recommendations. Fable's recommender today is a collaborative-filtering model built in house. It has served readers well, but it has no real-time signals and no learned ranking, and it can't recommend to new or lapsed readers. Your first big project is to move Fable onto Orion, so Fable and Everand share a modern recommendation stack. Key Responsibilities Lead the migration of Fable's recommendations onto Orion, covering data, features, training, serving and experiments, while keeping today's recommendations running. Extend Orion's rankers, feature store and embedding-based retrieval to support Fable, in partnership with the Orion ML platform team. Own the health of Fable's recommendation systems in production: quality, latency, cost and on-call. Bring Fable's social signals (shelves, ratings, reviews, book clubs, reader similarity) into recommendations for both Fable and Everand. Design and analyze A/B tests with product managers and analysts to decide what ships. Act as technical lead for Premium recommendations. Shape the roadmap with product managers, and see work that depends on other teams' systems through to delivery. Raise the bar on engineering practice in the squad through design reviews, code quality and operational readiness. Tech you'll work with You'll work across two stacks: Fable's on Google Cloud and Orion's on AWS. Fable: Python (FastAPI, Django), PostgreSQL, BigQuery, Kubernetes, Google Cloud including Vertex AI Orion and Everand: Python, Go and gRPC, Ruby on Rails, Databricks and Spark, Airflow, AWS SageMaker, Weaviate for embedding-based retrieval, feature store and model registry Infrastructure: AWS (EKS, ECS, Lambda, SQS, ElastiCache), Datadog, Terraform Requirements Must have 5+ years as a professional ML or software engineer, with a track record of shipping production ML systems. Hands-on experience building and running recommender systems in production, such as collaborative filtering or matrix factorization, two-tower or embedding retrieval, and learned ranking. Experience with large-scale data processing (Spark, Databricks, BigQuery or similar). Experience on at least one major cloud (AWS or GCP), including deploying services on containers (Kubernetes, ECS or similar). Experience designing and analyzing online experiments. A record of leading projects that depend on other teams, and of working directly with product managers. Bachelor's or Master's degree in Computer Science, or equivalent professional experience. Nice to have Google Cloud experience, especially Vertex AI and BigQuery. Experience migrating or replacing a production ML system while keeping it running. Social or graph-based recommendations, such as user similarity, follows or groups. Search and semantic retrieval (Elasticsearch, Vertex AI Search, vector databases). Experience on consumer apps for reading, media or social. At Scribd, Inc. your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States. In the state of California, the reasonably expected salary range is between $170,000 [minimum salary in our lowest geographic market within California] to $265,000 [maximum salary in our highest geographic market within California]. In the United States, outside of California, the reasonably expected salary range is between $140,000 [minimum salary in our lowest US geographic market outside of California] to $252,000 [maximum salary in our highest US geographic market outside of California]. In Canada, the reasonably expected salary range is between 179,000 CAD[minimum salary in our lowest geographic market] to 237,500 CAD[maximum salary in our highest geographic market]. We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Working at Scribd, Inc. Are you currently based in a location where Scribd, Inc. can employ you? Employees must have their primary residence in or near one of the following cities. This includes surrounding metro areas or locations within a typical commuting distance: United States Atlanta | Austin | Boston | Dallas | Denver | Chicago | Houston | Jacksonville | Los Angeles | Miami | New York City | Phoenix | Portland | Sacramento | Salt Lake City | San Diego | San Francisco | Seattle | Washington D.C. Canada Ottawa | Toronto | Vancouver Mexico Mexico City Benefits At Scribd, Inc. Scribd Flex (flexible work model) Comprehensive health, dental, and vision coverage Mental health support and disability coverage Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals Paid parental leave and family support benefits Retirement matching and employee equity Learning and development programs and professional growth opportunities Wellness and home office stipends Complimentary access to the Scribd, Inc. suite of products Enterprise access to leading AI tools Get to Know Scribd, Inc. About Scribd, Inc. Life at Scribd, Inc. We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing accommodations@scribd.com about the need for adjustments at any point in the interview process. If you apply for a job with Scribd, Inc. or otherwise engage with us in connection with employment (including as an employee, contractor, or other personnel), the personal information we process in that context is subject to our Employee and Applicant Privacy Policy, which is available here . Scribd, Inc. is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.

Scribd, Inc. is on a mission to advance human understanding. Our four products — Scribd®, Slideshare®, Everand™, and Fable — help billions of people across the globe move beyond access and into insight, application, and expertise. Culture at Scribd, Inc. We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. We believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in-person moments that strengthen collaboration and culture. Occasional in-person attendance is required for all Scribd, Inc. employees, regardless of location. So what are we looking for in new team members? At Scribd, Inc., we hire for "GRIT." Traditionally defined as the intersection of passion and perseverance toward long-term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude. This posting reflects an approved, open position within the organization. About The Team Premium is the Scribd Inc. pillar behind two reading products: Everand, the audiobook and ebook subscription app, and Fable, the social app where readers track, discuss and discover books. Helping readers find their next book is central to both, so search and recommendations sit at the heart of the products. You'll join Premium's new Discovery squad. It's a small, dedicated group of recommendations, search, applied research and ML engineers working full time on discovery for Everand and Fable. The squad works closely with Orion, Scribd's ML platform team. Orion runs the feature store, model registry, embedding-based retrieval and model serving behind discovery across Scribd, Slideshare and Everand. Role Overview We're looking for a Senior Machine Learning Engineer to own recommendations for Fable and grow into the technical lead for Premium recommendations. Fable's recommender today is a collaborative-filtering model built in house. It has served readers well, but it has no real-time signals and no learned ranking, and it can't recommend to new or lapsed readers. Your first big project is to move Fable onto Orion, so Fable and Everand share a modern recommendation stack. Key Responsibilities Lead the migration of Fable's recommendations onto Orion, covering data, features, training, serving and experiments, while keeping today's recommendations running. Extend Orion's rankers, feature store and embedding-based retrieval to support Fable, in partnership with the Orion ML platform team. Own the health of Fable's recommendation systems in production: quality, latency, cost and on-call. Bring Fable's social signals (shelves, ratings, reviews, book clubs, reader similarity) into recommendations for both Fable and Everand. Design and analyze A/B tests with product managers and analysts to decide what ships. Act as technical lead for Premium recommendations. Shape the roadmap with product managers, and see work that depends on other teams' systems through to delivery. Raise the bar on engineering practice in the squad through design reviews, code quality and operational readiness. Tech you'll work with You'll work across two stacks: Fable's on Google Cloud and Orion's on AWS. Fable: Python (FastAPI, Django), PostgreSQL, BigQuery, Kubernetes, Google Cloud including Vertex AI Orion and Everand: Python, Go and gRPC, Ruby on Rails, Databricks and Spark, Airflow, AWS SageMaker, Weaviate for embedding-based retrieval, feature store and model registry Infrastructure: AWS (EKS, ECS, Lambda, SQS, ElastiCache), Datadog, Terraform Requirements Must have 5+ years as a professional ML or software engineer, with a track record of shipping production ML systems. Hands-on experience building and running recommender systems in production, such as collaborative filtering or matrix factorization, two-tower or embedding retrieval, and learned ranking. Experience with large-scale data processing (Spark, Databricks, BigQuery or similar). Experience on at least one major cloud (AWS or GCP), including deploying services on containers (Kubernetes, ECS or similar). Experience designing and analyzing online experiments. A record of leading projects that depend on other teams, and of working directly with product managers. Bachelor's or Master's degree in Computer Science, or equivalent professional experience. Nice to have Google Cloud experience, especially Vertex AI and BigQuery. Experience migrating or replacing a production ML system while keeping it running. Social or graph-based recommendations, such as user similarity, follows or groups. Search and semantic retrieval (Elasticsearch, Vertex AI Search, vector databases). Experience on consumer apps for reading, media or social. At Scribd, Inc. your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States. In the state of California, the reasonably expected salary range is between $170,000 [minimum salary in our lowest geographic market within California] to $265,000 [maximum salary in our highest geographic market within California]. In the United States, outside of California, the reasonably expected salary range is between $140,000 [minimum salary in our lowest US geographic market outside of California] to $252,000 [maximum salary in our highest US geographic market outside of California]. In Canada, the reasonably expected salary range is between 179,000 CAD[minimum salary in our lowest geographic market] to 237,500 CAD[maximum salary in our highest geographic market]. We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Working at Scribd, Inc. Are you currently based in a location where Scribd, Inc. can employ you? Employees must have their primary residence in or near one of the following cities. This includes surrounding metro areas or locations within a typical commuting distance: United States Atlanta | Austin | Boston | Dallas | Denver | Chicago | Houston | Jacksonville | Los Angeles | Miami | New York City | Phoenix | Portland | Sacramento | Salt Lake City | San Diego | San Francisco | Seattle | Washington D.C. Canada Ottawa | Toronto | Vancouver Mexico Mexico City Benefits At Scribd, Inc. Scribd Flex (flexible work model) Comprehensive health, dental, and vision coverage Mental health support and disability coverage Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals Paid parental leave and family support benefits Retirement matching and employee equity Learning and development programs and professional growth opportunities Wellness and home office stipends Complimentary access to the Scribd, Inc. suite of products Enterprise access to leading AI tools Get to Know Scribd, Inc. About Scribd, Inc. Life at Scribd, Inc. We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing accommodations@scribd.com about the need for adjustments at any point in the interview process. If you apply for a job with Scribd, Inc. or otherwise engage with us in connection with employment (including as an employee, contractor, or other personnel), the personal information we process in that context is subject to our Employee and Applicant Privacy Policy, which is available here . Scribd, Inc. is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Summary: This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences. Job Description: Essential Responsibilities: Develop and optimize machine learning models for various applications. Preprocess and analyze large datasets to extract meaningful insights. Deploy ML solutions into production environments using appropriate tools and frameworks. Collaborate with cross-functional teams to integrate ML models into products and services. Monitor and evaluate the performance of deployed models. Minimum Qualifications: 3+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn. Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment. Several years of experience in designing, implementing, and deploying machine learning models. Additional Responsibilities & Preferred Qualifications: Subsidiary: PayPal Travel Percent: 0 The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is: Primary Location : Pay Range: San Jose, California: ($159,500.00 - $236,500.00 Annually) Additional Location(s) : Pay Range: No other locations are assigned to this requisition currently. Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable. PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important asset-you. That's why we offer comprehensive, choice-based programs, to support all aspects of personal wellbeing—physical, emotional, and financial—delivering meaningful value where it matters most. We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health. Who We Are: Click Here to learn more about our culture and community. Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.

Machine Learning Engineer Join an industry-leading life sciences technology organization that develops advanced software and AI solutions used by pharmaceutical, biotechnology, and research organizations worldwide. Their flagship AI platform brings cutting-edge machine learning directly into the workflows scientists use every day, helping drug discovery teams make faster, data-driven decisions. The platform combines large-scale scientific datasets, predictive modeling, and cloud-based infrastructure to accelerate the identification and development of new therapies. About The Role We are seeking a product-focused Machine Learning Engineer to help build and scale a next-generation AI platform used in drug discovery and scientific research. This individual will work across the full machine learning lifecycle, from data preparation and experimentation through model development, deployment, and optimization. You will collaborate closely with software engineers, scientists, and product teams to transform advanced machine learning research into reliable, production-ready solutions that deliver real-world impact. What You'll Do Design, build, and deploy machine learning models that support scientific discovery and predictive analytics. Develop solutions involving graph neural networks, transfer learning, molecular prediction models, and modern deep learning techniques. Create scalable training, evaluation, and model selection pipelines. Curate and improve large scientific datasets while ensuring data quality and reproducibility. Partner with engineering teams to deploy containerized ML services in cloud-based environments. Research and evaluate emerging machine learning approaches for incorporation into the platform. Qualifications 5+ years of experience building and delivering machine learning solutions in production environments. Strong Python development skills. Deep experience with PyTorch, TensorFlow, JAX, or similar frameworks. Strong understanding of model training, evaluation, optimization, and deployment. Experience translating complex machine learning problems into measurable business outcomes. Preferred Experience in life sciences, chemistry, drug discovery, bioinformatics, or related scientific domains. Knowledge of RDKit, Chemprop, federated learning, Kubernetes, Docker, and cloud-based ML infrastructure. This is an opportunity to work on highly impactful AI products that directly support scientific innovation and the development of life-changing therapies. Compensation: $180,000 - $250,000 base salary (Based on experience) plus benefits and equity If you are interested, please apply directly for immediate consideration or reach out to Brian Samela at bsamela@talener.com

About Canals Canals builds software for wholesale distributors, helping them operate more efficiently through automation and AI. Our customers are the companies responsible for moving the materials that power the real economy; electrical supplies, plumbing products, roofing materials, HVAC equipment, and more. Every day, thousands of people rely on Canals to help process orders, manage purchasing, handle accounts payable, and streamline critical business workflows. We're a profitable, rapidly growing company with a team of roughly 140 people distributed across North and South America. We care deeply about building great products, hiring exceptional people, and creating an environment where talented individuals can do the best work of their careers. The Role Our customer base is expanding fast, and AI is central to how we scale and deliver value. We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world impact. What You'll Do Design, build, and maintain scalable machine learning models that improve and automate logistics processes for our customers. Own projects end-to-end, from problem definition and data exploration to model deployment and monitoring in production. Collaborate closely with engineering teams to align ML work with customer needs and deliver features that drive business value. Serve as a technical leader and mentor within the ML area, reviewing code and ensuring best practices for reproducibility, quality, and performance. Evaluate and implement tools and frameworks to improve our ML infrastructure and workflows. Help shape the future of Canals as we continue scaling with our customers. What You'll Bring Senior-level experience building and deploying machine learning models in production environments. Experience designing scalable data pipelines and working with large datasets. Comfort taking ownership of projects and ensuring models deliver real, measurable customer value. Strong Python skills with knowledge of ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow) and data tools (e.g., Pandas, Spark). Ability to guide and unblock others, providing thoughtful code reviews and architectural feedback. Experience working independently in a fast-paced, product-focused environment. Previous experience in high-growth startups or small teams is a plus. Familiarity with MLOps practices and tools is a plus. Why Join Canals We're building software that solves real problems for an industry that keeps the world running. Our customers rely on our platform every day to operate their businesses. We've found strong product-market fit and continue to grow quickly, creating opportunities for people who want to have a meaningful impact on the trajectory of a company. We believe great people build great companies. That's why we invest heavily in hiring, development, and creating an environment where talented individuals can do the best work of their careers. You'll work alongside ambitious, thoughtful teammates who care deeply about what they do, challenge each other directly, and have a lot of fun along the way. We value ownership, transparency, and continuous improvement. Good ideas can come from anywhere, and people are trusted to make things happen. We're remote-first, flexible, and distributed across North and South America, bringing together talented people from a wide range of backgrounds and experiences. Canals.ai is an equal opportunity employer. In addition to EEO being the law, it is a policy that is fully consistent with our principles. All qualified applicants will receive consideration for employment without regard to status as a protected veteran or a qualified individual with a disability, or other protected status such as race, religion, color, national origin, sex, sexual orientation, gender identity, genetic information, pregnancy or age.

Overview Working at Atlassian Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Responsibilities Design, develop, and train cutting-edge world class machine learning models (including NER, personalization, prediction, and LLM fine-tuning) to power Atlassian products. Ship production-ready ML systems by collaborating with engineering, product, and analytics teams to integrate AI features into Atlassian services as well as performing machine learning model optimization techniques and writing production quality code. Conduct experimentation and model evaluation, ensuring performance, scalability, and reliability of deployed models. Define and monitor product metrics, using data analysis to guide improvements and measure impact. Contribute to Atlassian's next-gen AI initiatives, including foundational model development and researching and advancing the state of ML techniques to land new unique features for Atlassian's AI offerings. Communicate findings and recommendations to senior leaders through clear presentations and insights. 40 hrs/week, Mon-Fri, 8:30 a.m. - 5:30 p.m. Salary: $276,200/yr. Compensation At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range. Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter. This role may also be eligible for benefits, bonuses, commissions, and equity. Qualifications MINIMUM REQUIREMENTS: Master's degree or foreign equivalent degree in Computer Science, Electrical Engineering, or a related field of study, and three (3) years of related work experience. Must Have Three (3) Years Of Experience With/in Spark and Cloud data environments (AWS, Databricks, or Azure) Building and scaling machine learning models using large amounts of data Utilizing Python or Java to write performant production-quality code Anomaly detection for dataset analysis for the purpose of training, validating, and shipping machine learning models Agile development practices SQL BI tooling using Tableau, Excel, Power BI, or Looker 100% Telecommuting is permitted. Please email resume to: postings@atlassian.com and must reference Job code: "CA013" to be considered Benefits & Perks Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits . About Atlassian At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them. To learn more about our culture and hiring process, visit go.atlassian.com/crh . In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.