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ABS Group is seeking an AI/ML Engineer to join our Artificial Intelligence Practice in support of a major federal modernization program. In this role, you will design, develop, and operationalize machine learning and artificial intelligence solutions that support mission applications and data-driven workflows. You will help bring AI capabilities into production, build supporting pipelines and model operations workflows, and work across data science, engineering, and cloud teams to deliver scalable, secure, and trustworthy AI solutions. The scope of responsibility, degree of technical leadership, and level of independence expected will reflect the level at which this position is filled. What You Will Do Design, develop, and operate AI and machine learning capabilities for production applications and data workflows Build and maintain data and model pipelines that support training, deployment, monitoring, and lifecycle management Partner with data scientists, developers, and cloud engineers to productionize AI solutions Implement MLOps and related engineering practices for model deployment, monitoring, retraining, and version control Support generative AI and large language model implementations, including prompt workflows, retrieval-augmented generation, and vector-based retrieval patterns Apply AI/ML to adjacent use cases such as test automation, workflow support, and operational optimization Contribute to CI/CD, observability, and operational support for AI systems in secure environments Support responsible AI and model governance practices, including explainability and compliance requirements Document architectures, workflows, and engineering standards for project delivery What You Will Need Level and Compensation: This position may be filled at multiple career levels based on business need and the selected candidate's qualifications, relevant experience, and demonstrated capability. Typical leveling for this role is as follows: Junior (0 to 4 years) Mid-Level (5 to 9 years) Senior (10 to 14 years) Principal (15 or more years) These ranges are guidelines only and are not the sole determining factor in level. The posted compensation range reflects the full range across all possible levels. Individual offers will be based on the level at which the candidate is hired, as well as factors such as skills, experience, internal equity, and geographic market considerations where applicable. Education and Experience Bachelor's degree in Computer Science, Data Science, Software Engineering, Engineering, or a related technical field; Master's degree preferred Relevant professional experience in AI engineering, machine learning engineering, or related software engineering roles; the depth and scope of experience required will vary based on the level at which this position is filled Experience deploying or supporting machine learning and AI systems in production environments preferred Experience working in cloud-based or hybrid technical environments preferred Knowledge, Skills, and Abilities Proficiency in Python Familiarity with frameworks such as TensorFlow, PyTorch, and scikit-learn Familiarity with MLOps, CI/CD for ML, and model monitoring concepts and practices Exposure to LLMOps, AIOps, RAG, and vector databases Experience building or supporting data pipelines for AI/ML applications Understanding of software engineering and DevSecOps practices for production systems Strong collaboration skills across technical teams and stakeholders Nice to Have Experience supporting production ML at scale Experience with AWS, Azure, or GCP AI/ML services Familiarity with federal, public sector, or regulated AI environments Exposure to NLP, classification, survey analytics, or entity resolution use cases Location This position is based in the Washington, D.C. metro area, with primary work performed in Suitland, Maryland. Remote or hybrid arrangements may be available for eligible work, subject to government approval. Notice: This role has been opened for a future need expected within three months of the original posting date of this position. Potential candidates may not receive communication until the open headcount is confirmed.

Our Company Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, and data they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits, and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together. Position Summary As an AI/ML Engineer , you will join our innovative technology team at Optum Technology to design, build, and deploy cutting-edge artificial intelligence and machine learning capabilities that transform healthcare operations. In this role, you will develop scalable GenAI models, Large Language Model (LLM) applications, agentic frameworks, and robust Python inference APIs deployed on Kubernetes infrastructure. Working in a fast-paced, collaborative environment, you will leverage modern developer tools and semantic search capabilities to deliver highly accessible, impactful AI solutions across enterprise healthcare data. You'll enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges. Primary Responsibilities Design, develop, and validate machine learning models using GenAI (LLMs, agentic frameworks) and traditional ML techniques on cloud platforms Write and deploy scalable Python APIs for model inference running on Kubernetes, ensuring efficient containerization and orchestration of agentic flows Implement and integrate semantic search capabilities to enhance data accessibility and retrieval for analytics and business intelligence Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AI Evaluate emerging technology trends and best practices to inform solution design, architecture, and strategic innovation Leverage enterprise-approved AI tools to streamline developer workflows, automate tasks, and drive continuous software delivery improvement Utilize agentic coding and version control tools (e.g., GitHub Copilot, Claude) for efficient code creation, repository management, and technical collaboration Maintain rigorous coding standards, thorough documentation, and effective performance monitoring across all deployed AI/ML pipelines You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear directions on what it takes to succeed in your role as well as provide development for other roles you may be interested in. Required Qualifications 4+ years of software development, data engineering, or AI/ML experience 4+ years of professional experience in Python using core data science and machine learning libraries (e.g., scikit-learn, Databricks) 3+ years of experience applying machine learning techniques in a commercial enterprise, including supervised/unsupervised learning, time-series forecasting, or statistical analysis 2+ years of experience applying NLP (transformers, GPT) or LLMs (RAG, vector databases, embeddings) in a production setting with large-scale datasets 1+ years of experience building, deploying, and maintaining RESTful APIs for machine learning model inference Preferred Qualifications Bachelor's degree or equivalent experience Strong analytical, quantitative, problem-solving, and critical thinking skills Strong written and verbal communication skills, including the ability to present detailed technical analyses to diverse technical and business stakeholders Experience with vision and speech models in GenAI (multimodal architectures) Background in healthcare data analytics (e.g., claims, eligibility, enrollment) and working within regulated compliance environments Hands-on experience with containerization and container orchestration technologies such as Docker and Kubernetes Experience utilizing AI-assisted developer and coding tools to accelerate software production and technical documentation Demonstrated familiarity with agentic frameworks, Model Context Protocol (MCP), and Agent-to-Agent (A2A) architectures All Telecommuters will be required to adhere to UnitedHealth Group's Telecommuter Policy. Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $98,500 to $176,000 annually based on full-time employment. We comply with all minimum wage laws as applicable. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants. At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location, and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups, and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission. UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group is a drug-free workplace. Candidates are required to pass a drug test before beginning employment. #RPO #GREEN

Our Mission Rebuild how the world works, to make institutions work better for the people they serve. About Brain Co. Brain Co. builds AI-native operating systems for large, regulated institutions. Each system is built for a specific industry, powered by agents that push real workflows forward. Underneath it all is Atlas, our proprietary platform that keeps customers in control, secure by design, and never locked into one model. Why Now Brain Co. is entering its next phase of production deployments on a national scale with an elite team built from Palantir, Google, Meta, and Nvidia, and a growing footprint across government, insurance, health, and financial services. Joining now means shaping both the company and a new category of applied AI. Every project here ships to production and is expected to create measurable customer value and impact. You'll work alongside exceptional peers on some of the hardest problems in applied AI. It's the kind of work you'll still be proud of in ten years from now. At Brain Co., new-grad engineers contribute to real production systems and see their work deployed at global scale. About The Role As a Machine Learning Engineer at Brain Co., you will play a crucial role in deploying state-of-the-art models to automate various real world problems in sectors such as healthcare, government and energy. Part of the role will involve turning research breakthroughs into practical solutions for various nation states. This role is your opportunity to make a significant impact by making AI technology both accessible and influential. What You'll Work On Innovate and Deploy: Design and deploy advanced LLM models to tackle real-world problems, particularly in automating complex, manual processes in a range of real-world verticals. Optimize and Scale: Build scalable data pipelines, optimize models for performance and accuracy, and prepare them for production. Monitor and maintain deployed models to ensure they continue delivering value across various governments worldwide. Make a Difference: Engage in projects including but not limited to optimizing the world's most advanced energy production systems, modernizing core government workflows, or improving patient outcomes in advanced public healthcare systems. Your work will directly impact how AI benefits individuals, businesses, and society at large. Engage with Leaders: interact directly with government officials in various countries and apply the first of its kind AI solutions while working alongside experienced ex. Founders, AI researchers, and software engineers to understand complex business challenges and deliver AI-powered solutions. Join a dynamic team where ideas are exchanged freely and creativity flourishes. You will be able to wear many hats: software building, product management, sales, interpersonal skills. Learn and Lead: Keep abreast of the latest developments in machine learning and AI. Participate in code reviews, share knowledge, and set an example with high-quality engineering practices. You Might Be a Great Fit If You… Expect to complete a bachelor's degree in Computer Science, Engineering, Machine Learning, Data Science, or a related field in Spring 2027. Have hands-on experience building GenAI-focused applications (e.g., agents, reasoning workflows, or RAG) and a solid understanding of how large language models are architected and operated. Have personally implemented models in common ML frameworks such as PyTorch, Jax or TensorFlow. Possess a strong foundation in data structures, algorithms, and software engineering principles. Exhibit excellent problem-solving and analytical skills, with a proactive approach to challenges. Can work collaboratively with cross-functional teams. Thrive in fast-paced environments where priorities or deadlines may compete. Are eager to own problems end-to-end and willing to acquire any necessary knowledge to get the job done. Job Details & Benefits Eligibility: Completing a bachelor's degree in Spring 2027. Competitive full-time compensation and benefits Support and feedback from experienced platform engineers Opportunity to work on real production systems used globally Meaningful ownership from day one, with room to grow alongside the team Daily lunches (if onsite)

We are Lenovo. We do what we say. We own what we do. We WOW our customers. Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world's largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo's continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY). This transformation together with Lenovo's world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub. We are seeking a highly motivated AI Developer – New Graduate to join our US engineering team. This role is based in Morrisville, NC and operates under a hybrid policy. The target start date will be January 2027. This is an entry-level role designed for recent graduates with a strong software engineering foundation and hands-on exposure to AI/ML or Generative AI through internships, research, academic projects, or personal projects. You will participate in the design and development of enterprise AI applications using technologies such as LLMs, RAG, AI Agents, tool/function calling, embedding/vector search, and AI workflow orchestration. This is not a purely research-focused AI position. You will work on real enterprise products and collaborate with product managers, architects, developers, and business stakeholders throughout the solution lifecycle. We are particularly interested in candidates with the potential to grow into an FDE-style engineer — someone who can combine strong technical execution with business understanding, customer communication, rapid problem solving, and end-to-end ownership. Job Responsibilities Design, develop, test, and enhance enterprise AI applications and AI-enabled product capabilities. Build solutions involving LLMs, RAG, AI Agents, prompt engineering, tool/function calling, vector/embedding search, and AI workflow orchestration. Develop backend services, APIs, data integrations, and other components required to connect AI capabilities with enterprise systems. Participate in AI evaluation, testing, debugging, and performance improvement to continuously improve solution quality, reliability, latency, and user experience. Work with product managers, architects, business stakeholders, and engineering teams to understand business problems and translate requirements into practical technical solutions. Participate in requirement discussions, solution design, technical reviews, demos, UAT support, and production deployment. Prototype and evaluate new AI technologies and quickly determine their feasibility for real business scenarios. Troubleshoot technical and production issues and continuously improve application stability and engineering quality. Develop a strong understanding of business processes and user journeys rather than focusing only on individual technical tasks. Gradually take greater ownership of solutions from problem definition and prototyping through implementation and delivery. For candidates demonstrating strong technical and communication capabilities, gradually develop toward an FDE role, directly partnering with stakeholders to explore problems, prototype solutions, and drive AI use cases from concept to production. Basic Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related technical field. Recent graduate or early-career candidate with strong academic, internship, research, or project experience. Strong programming fundamentals, with hands-on experience in Python. Hands-on project, research, or internship experience in at least one AI-related area such as: Large Language Models (LLMs) Generative AI applications RAG AI Agents AI chatbot / conversational AI NLP Machine Learning Embedding / vector search Tool / Function Calling AI automation Ability to clearly explain the architecture, implementation, challenges, and results of AI or software projects you have personally worked on. Good understanding of software engineering fundamentals, including APIs, databases, debugging, source control, and software development lifecycle. Strong learning ability and curiosity about new AI technologies. Strong problem-solving skills and willingness to work through ambiguous problems. Good verbal and written communication skills, with the ability to collaborate with both technical and non-technical stakeholders. Strong ownership mindset and willingness to learn business processes in addition to technology. Ability to work effectively in a global, cross-functional engineering environment. Preferred Qualifications Master's degree in Computer Science, AI, Machine Learning, Data Science, or a related field. Internship or project experience building production-oriented LLM or Generative AI applications. Experience with frameworks or technologies such as LangChain, LangGraph, AutoGen, Hugging Face, PyTorch, or similar AI development frameworks. Experience with RAG pipelines, vector databases, embeddings, Agent workflows, or tool/function calling. Experience with backend development using Python frameworks such as FastAPI or Flask. Familiarity with relational databases, SQL, REST APIs, cloud platforms, Docker, or Kubernetes. Experience developing and evaluating AI prototypes and converting prototypes into usable applications. Exposure to LLM evaluation, prompt evaluation, test datasets, or AI observability is a plus. Experience working directly with users, customers, product teams, or business stakeholders through internships, university projects, startup experience, or other activities. Demonstrated ability to independently explore an unfamiliar problem, quickly build a prototype, collect feedback, and iterate on the solution. Interest and potential to grow toward a Forward Deployed Engineer (FDE) role combining engineering, product thinking, business understanding, and stakeholder engagement. Mandarin Chinese communication skills are a plus due to frequent collaboration with China-based engineering teams. We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.

About FullStack FullStack is your AI-native engineering partner, built to turn AI capability into certainty. Most companies can demo AI; few can get it to production and prove what it produced. We close that gap with three capabilities, AI built into your products from the start, elite vetted talent who apply it, and transparent execution that shows value every step of the way. With now over 600 customers in North America, FullStack is one integrated partner for all your AI engineering needs. With FullStack, you move forward with confidence. We're Most Proud Of Offering life-changing career opportunities to talented software professionals across the Americas. Building highly-skilled software development teams for hundreds of the world's greatest companies. Having delivered hundreds of successful custom software solutions, which have positively impacted the lives and careers of millions of users. Our 4.1-star rating on GlassDoor. Our client Net Promoter Score of 68, twice the industry average. The Position We're Looking To Hire a Senior Machine Learning Engineer (Traditional ML & Financial Data) To Join Our Team. You'll Work With Our Incredible Clients In One Of Two Ways Team Augmentation: You will integrate yourself directly into our client's team and work alongside their existing designers and engineers on a daily basis. Design & Build: You will work on a FullStack product team to build and deliver a product to our clients. What We're Looking For 5+ years of professional experience in software development, Data Science, or Machine Learning Engineering. Advanced English is required. Successful completion of a four-year college degree is required. Strong expertise in traditional machine learning algorithms and statistical modeling, with a focus on non-LLM and non-Generative AI approaches. Hands-on experience designing, developing, training, and optimizing machine learning models for production use. Strong proficiency in data exploration, preprocessing, feature engineering, and model training using complex datasets. Demonstrated experience developing and optimizing anomaly detection algorithms to identify irregularities, patterns, and outliers in data. Strong Python skills and experience with relevant machine learning and data science libraries. Experience analyzing financial, payroll, or other structured business datasets is highly preferred. Proactive, ownership-driven mindset with strong analytical and problem-solving skills, capable of translating complex data into reliable machine learning solutions. Ability to work through new and difficult issues and contribute to libraries as needed. Ability to create and maintain continuous integration and delivery of applications. Forensic attention to detail. A positive mindset and a can-do attitude. Experience working on Agile/Scrum teams. Meaningful experience working on large, complex systems. Ability to take extreme ownership over your work. Every day is a challenge to ensure you are performing to the expectations you and your team have agreed upon. Ability to identify with the goals of FullStack's clients, and dedicate yourself to delivering on the commitments you and your team make to them. Nice To Have We're Seeking Engineers Who Are AI-enthusiastic In Their Workflow. Professional Experience Or Personal Project Work With The Following Is a Significant Plus Cursor, Windsurf, or Google Antigravity. Claude Code, Gemini CLI, Codex, or Copilot CLI. Work Authorization Requirements Applicants must be currently authorized to work in the United States on a full-time basis. FullStack will not sponsor applicants for work visas now or in the future. What We Offer Competitive Salary. Paid Time Off (vacation, sick leave, parental leave, and holidays). 100% remote work. The ability to work with leading startups and Fortune 500 companies. Health, dental, and vision insurance. 401(k) w/ 4% match. Ample opportunity for career advancement. Continuing education opportunities. FullStack is proud to be an equal opportunity workplace. We are 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. Learn more about our Applicants Privacy Notice.

About NewsBreak Local life runs on local information. What happened down the street? Who can fix this? Where should we go tonight? NewsBreak started in 2015 to answer these questions, and today more than 40 million people a month rely on us to follow what's going on in their zip code. Three platforms with one vision: powering local life. Led by founder and CEO Jeff Zheng, NewsBreak is our local life and news platform; Nearby AI connects people with local businesses; and NDot AI helps publishers and creators grow and earn. Building for the long term. A $115 million Series C made us a unicorn in 2021, and we keep investing in our people. We're Great Place to Work® certified and named to Fast Company 's Best Workplaces for Innovators (2025) and Fortune 's Best Workplaces in the Bay Area™ (2026). Everyone makes an impact. Whether you write code, shape products, tell our story, or run the business, we want people who own projects end to end, stay curious, and speak up. Join us. Learn more at: NewsBreak, Nearby AI, NDot AI About The Role We are looking for a Machine Learning Engineer to build intelligent systems that connect consumers with relevant local information, businesses, and services. You will work across areas such as search, recommendation, ranking, retrieval, user-intent understanding, personalization, and marketplace matching. Depending on your background and interests, you may focus on understanding consumer demand, improving search and recommendation relevance, or building models that more effectively match users with local supply. This is a hands-on role with the opportunity to take machine learning solutions from problem definition and experimentation through production deployment and iteration. We welcome candidates across a range of experience levels, and the scope and level of the role will be calibrated based on the candidate's experience. What You'll Do Build and improve machine learning models for search, recommendation, ranking, retrieval, matching, and personalization. Develop systems that understand user queries, behaviors, preferences, and context. Apply embeddings, natural language processing, large language models, and modern retrieval techniques to connect consumer demand with relevant local content, businesses, or services. Build and optimize end-to-end ML pipelines, from data preparation and model training to online serving and monitoring. Partner with product, engineering, and data teams to define problems, identify opportunities, and translate business needs into scalable ML solutions. Design and analyze online and offline experiments to measure model quality and product impact. Improve key product outcomes such as relevance, engagement, conversion, retention, and marketplace efficiency. Explore new ML and LLM techniques and bring them into production where they can deliver measurable value. What We're Looking For Experience building machine learning, data mining, search, recommendation, ranking, NLP, or related systems through academic projects, internships, or industry work. Strong programming skills in Python, Java, C++, or another relevant language. Solid understanding of machine learning fundamentals, data structures, algorithms, and statistical analysis. Experience with one or more of the following: Search, retrieval, or learning-to-rank Recommendation or personalization Query understanding, intent classification, or NLP Embeddings, semantic search, or large language models Matching, marketplace optimization, or dispatch Ability to work with large-scale or complex datasets and translate ambiguous problems into practical solutions. Strong collaboration and communication skills. Interest in building production systems that serve real users and deliver measurable product impact. Nice to Have Experience deploying and maintaining machine learning models in production. Experience with experimentation, including A/B testing, causal analysis, or marketplace experiments. Familiarity with deep learning frameworks and ML infrastructure, such as PyTorch, TensorFlow, Spark, Kubernetes, or feature and model-serving platforms. Experience building taxonomies, user-interest representations, knowledge graphs, or behavioral models. Experience applying LLMs to search, recommendation, classification, or information retrieval. Background in local search, local services, maps, commerce, marketplaces, delivery, mobility, or location-based products. Experience at a consumer internet, search, recommendation, advertising, e-commerce, or marketplace company. Annual Base Pay Range $190,000 - $300,000 The US base salary range for this full-time position will vary based on job-related skills, level, experience, geographic location, and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talent. Depending on the position and level, the role may also be eligible for a discretionary bonus and equity. Your recruiter can share more details during the hiring process. The US base salary range for this full-time position is listed below. Pay may vary based on a number of factors including job-related skills, level, experience, geographic location and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talents. Depending on the position, the role may also be eligible for discretionary bonus and options. Your recruiter can share more details during the hiring process. Annual Base Pay Range $190,000 - $300,000 USD CPRA Privacy Notice for California Candidates

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 lead the design, development, and implementation of advanced 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: Lead the development and optimization of advanced machine learning models. Oversee the preprocessing and analysis of large datasets. Deploy and maintain ML solutions in production environments. Collaborate with cross-functional teams to integrate ML models into products and services. Monitor and evaluate the performance of deployed models, making necessary adjustments. Minimum Qualifications: 5+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn. Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment. 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: ($196,500.00 - $291,500.00 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.

← Back to all positions AI/ML Engineer Active 📍 Hybrid - San Francisco🏢 AI & Research⏱ Full-time💼 3+ years📅 Posted: 2025-01-20⏳ Closes: 2025-03-20 As an AI/ML Engineer, you will design, train, and deploy machine learning models at scale. You'll work on NLP, computer vision, and recommendation systems that directly impact millions of users. 🎯Responsibilities Design and implement ML pipelines for training and inference Develop NLP and computer vision models Optimize model performance and reduce latency Collaborate with data engineers on data pipelines Stay current with the latest AI research and apply findings ✅Requirements 3+ years of experience in ML/AI engineering Proficiency in Python, PyTorch or TensorFlow Experience with LLMs and transformer architectures Strong understanding of MLOps and model deployment MS or PhD in Computer Science, ML, or related field preferred ⭐Nice to Have Published research papers Experience with RAG systems Familiarity with cloud platforms (AWS, GCP) 🎁Benefits Competitive salary Flexible hybrid work Conference and research budget Apply for this Position 👤 Personal Information Full Name Email Address Phone Number 🇺🇸 +1🇨🇦 +1🇮🇳 +91 GitHub Profile 💼 Professional Details Current Company Current Role / Title Years of ExperienceSelect experience0 – 1 year1 – 3 years3 – 5 years5 – 8 years Expected Salary (Annual) Notice PeriodSelect notice periodImmediately available1 month2 monthsMore than 2 months When Can You Start? How Did You Hear About Us?Select sourceLinkedInGitHubTwitter / XEmployee ReferralJob Board (Indeed, Naukri, etc.)Company WebsiteGoogle SearchOther 📄 Resume / CV 📤 Click to upload your resume PDF, DOC, DOCX — Max 5MB 💡 Tell Us More About You Why are you interested in this role? 0 / 2000 What makes you a good fit for this position?* 0 / 2000 Additional Cover Letter (Optional) 0 / 5000 By submitting this application, you agree to our privacy policy and consent to the processing of your personal data for recruitment purposes.

EvenUp is on a mission to close the justice gap using technology and AI. We empower personal injury lawyers and victims to get the justice they deserve. Our products enable law firms to secure faster settlements, higher payouts, and better outcomes for victims injured through no fault of their own in vehicle collisions, accidents, natural disasters, and more. We are one of the fastest-growing vertical SaaS companies in history, and we are just getting started. EvenUp is backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures, SignalFire, and Lightspeed. We are looking to expand our team with talented, driven, and collaborative individuals who seek to have a lasting impact. Learn more at www.evenuplaw.com. Machine Learning Engineer We're looking for a Machine Learning Engineer to join our ML team at EvenUp. You'll develop and deploy models that power Piai™, our proprietary claims-intelligence platform, with a focus on machine learning, natural-language processing, and generative AI. Working alongside senior ML engineers, data scientists, and legal subject-matter experts, you'll turn raw legal and medical data into production-ready models that directly improve outcomes for personal-injury clients. What You'll Do Explore, implement, and benchmark ML, NLP, and generative AI methods - including LLM fine-tuning, retrieval-augmented generation, and document understanding. Clean, annotate, and transform structured and unstructured case data, and build reusable datasets and data loaders. Design experiments, run A/B tests, analyze results, and communicate findings to product and engineering teams. Help integrate models into our production systems, partnering with ML platform engineers on testing, monitoring, and scaling. Pair with product managers, legal analysts, and software engineers to translate real problems into ML solutions and measurable improvements. Stay current with research in LLMs, representation learning, and prompt engineering, and share what you learn with the team. What You Bring B.S., M.S., or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, Computational Linguistics, or a related field. Solid grounding in ML fundamentals - supervised and unsupervised learning, evaluation metrics, overfitting and regularization. Hands-on experience with NLP or generative AI techniques - transformers, embeddings, sequence-to-sequence models, or LLMs. Proficiency in Python and ML/NLP libraries such as PyTorch, TensorFlow, Hugging Face, or spaCy. Familiarity with SQL and basic data engineering concepts - ETL, versioned datasets, notebooks. Strong analytical thinking, clear communication, and eagerness to learn and iterate quickly in a fast-moving startup. Ability to work hybrid (3 days your choice) in our San Francisco or Toronto, Canada office. Nice to Have Exposure to cloud platforms (AWS, GCP). Experience with experiment-tracking tools (Weights & Biases, Gemini Enterprise Agent Platform, MLflow). Familiarity with containerized deployment (Docker, Kubernetes). Experience in a high-growth startup environment. Benefits & Perks: As part of our total rewards package, we offer attractive benefits and perks to our employees, including: Choice of medical, dental, and vision insurance plans for you and your family. Additional insurance coverage options for life, accident, or critical illness. Flexible paid time off, sick leave, short-term and long-term disability. 10 US observed holidays, and Canadian statutory holidays by province. A home office stipend. 401(k) for US-based employees and RRSP for Canada-based employees. Paid parental leave. A local in-person meet-up program. Hubs in San Francisco and Toronto. (Please note the above benefits & perks are for full-time employees) Notice to Candidates: To ensure fairness and proper consideration, we do not accept resumes or expressions of interest via email or social media messages. If you're interested in a role, please submit your application directly through our careers page . Please note that EvenUp may use AI notetakers and other recording devices in the recruiting process. If you interview with us, with your consent, we may record your conversations and summarize them into notes for internal use. Recording is optional, and declining will not affect your candidacy. EvenUp is an equal opportunity employer. We are committed to diversity and inclusion in our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Compensation Range: $130K - $205K

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we're behind some of Spotify's most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you'll keep millions of users listening by making great recommendations to each and every one of them. The Surfaces Podcasts team owns podcast recommendations across some of Spotify's most visible surfaces, including Home and the Now Playing view. We build and improve the recommendation systems that help listeners discover their next favorite show or episode while helping creators reach the right audiences. As a Staff Machine Learning Engineer, you'll help shape the future of personalized discovery and engagement at Spotify. You'll work at the intersection of recommendation systems, large language models, and production-scale machine learning infrastructure to build experiences for listeners at global scale. You'll take models from research to production, help set technical direction in ambiguous problem spaces, and solve complex personalization challenges across Spotify. What You'll Do Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience. Design, build, and ship personalized recommendations that serve millions of Spotify listeners globally. Build content recommendation systems for emerging agentic and AI-powered user experiences. Train, fine-tune, evaluate, and optimize large language models using techniques such as supervised fine-tuning (SFT), distillation, and parameter-efficient training approaches. Partner closely with Product Managers, Engineers, Data Scientists, and Designers to define and execute experimentation strategies. Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality, reliability, and cost efficiency. Improve ML platform capabilities, data pipelines, and production systems that support personalization at Spotify scale. Drive technical direction in ambiguous problem spaces and contribute to the long-term architecture of our personalization systems. Mentor and support other Machine Learning Engineers, sharing knowledge and helping strengthen engineering practices across the team. Who You Are You have deep experience building and deploying machine learning systems in production environments. You have deep experience with recommendation systems, ranking models, personalization, or large-scale content discovery platforms. You are proficient in Python and have hands-on experience building machine learning systems with PyTorch. You have experience with large language model training, fine-tuning, evaluation, and optimization techniques, including SFT, distillation, and LoRA. You have worked with large-scale inference systems and understand the challenges of latency, reliability, and cost optimization. You care about creating high-quality user experiences through thoughtful applications of machine learning. You communicate effectively with technical and non-technical partners and can influence technical decisions beyond your immediate team. You know how to design, execute, and interpret online experiments and A/B tests to improve user outcomes. You have experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks. You have experience building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms. Where You'll Be We offer you the flexibility to work where you work best! For this role, you can be within the North Americas region as long as we have a work location. This team operates within the Eastern Standard time zone for collaboration. The United States base range for this position is $227,495- $324,993 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It's in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we're here to support you in any way we can. Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world's most popular audio streaming subscription service.

About The Team The Deliverability team sits at the core of Uber's delivery marketplace as part of Merchant Optimization. Serving as the critical gating layer for every Uber Eats transaction, our systems answer the fundamental real-time question: "Can this merchant deliver to this eater right now?" We optimize merchant delivery zones to maximize platform selection while balancing marketplace reliability, timeliness, and profitability. The decision made by the deliverability services directly shape selection breadth and business metrics across key downstream platforms, including Search, Feed, and Ads. Role & Responsibilities As a Senior Machine Learning Engineer on the Deliverability team, you will drive the technical vision, end-to-end design, and productionization of core ML systems powering global delivery marketplace decisions. Specifically, you will: Product & Domain ML Architecture: Architect and translate complex marketplace challenges into high-throughput, large scale ML solutions for delivery zone optimization. Design & Train Core Models: Develop, evaluate, and continuously refine state-of-the-art machine learning models that dynamically optimize merchant delivery coverage, balancing conversion, order volume, and fulfillment efficiency. Production Pipelines & ML Infrastructure: Engineer, deploy, and operate scalable ML inference pipelines, feature stores, model serving infrastructure, and automated retraining workflows handling high-throughput global delivery evaluations. Marketplace Optimization & Experimentation: Lead data-driven investigations to diagnose marketplace inefficiencies, execute online A/B testing and leverage telemetry to drive core business metrics. Cross-Functional Technical Leadership: Partner closely with Product Management, Data Science, Operations, and Core Infrastructure teams to align technical roadmaps and define cross-platform ML standards. Basic Qualifications 5+ years of hands-on professional experience designing, training, and operating production ML models at scale. Proactive and strong analytical mindset with a passion for uncovering insights from complex data distributions to drive technical decision-making and project buy-in. Advanced proficiency in Python and mainstream machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn). Solid theoretical foundation in classic and modern ML algorithms, including and not limited to gradient-boosted trees (XGBoost, LightGBM), deep neural networks, and statistical modeling. Proven record of taking complex ML systems end-to-end from initial problem formulation and offline validation to large-scale production deployment. Practical experience developing automated feature engineering pipelines, using feature store technologies, model monitoring platforms, and executing controlled online A/B testing in production. Preferred Qualifications PhD candidate 3+ years of industry experience Experience with geospatial libraries (e.g., H3, S2 Cell). Experience with Graph Neural Networks (GNNs), and/or deep learning recommendation systems. Demonstrated ability to drive cross-functional technical initiatives, mentor junior engineers, and deliver complex multi-phase engineering projects. Familiarity with distributed data processing systems (e.g., Spark, Ray, Flink) and foundational concepts in two-sided marketplace optimization. For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. Ready to Ride? This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you. You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits. Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

🚀 Join the Future of Commerce with Whatnot! Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops. As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact. We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce. 💻 Role We're looking for entrepreneurial software engineers who thrive on ambiguous, 0-to-1 work. You'll design and deploy both traditional ML models and infrastructure (contextual bandits to manage ad spend, shipment ETA predictions) and LLM-powered systems (RAG pipelines, human-in-the-loop evaluation frameworks) to address the business's most pressing problems. Your job will change every ~12 months as we hand off stable products and pivot to address the business's next big need. Strong applicants display exceptional business judgement and are equally comfortable contributing to production infrastructure and training the models that run on it. They build for the long term while finding ways to aggressively pull forward business impact. What You'll Do Develop and deploy new both production machine learning algorithms and core infrastructure to enrich the buyer and seller experience. Contribute to and set direction across the entire machine learning development process: opportunity sizing, feature engineering, model training, evaluation, load testing, deployment, and alerting. Design and implement supporting software infrastructure to unblock your work: streaming pipelines, async worker queues, event enrichment infrastructure, continuous training loops, model monitoring systems, LLM tool access controls, and dynamic agent evaluation framework to give just a few examples Define project roadmaps that deliver value quickly while building towards scalable, extensible long-term systems Bridge research and production: take an experimental idea and harden it into a scalable, well-tested, monitored system. Communicate tradeoffs and findings clearly to product and leadership. We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Seattle or San Francisco hub. 👋 You Curious about who thrives at Whatnot? We've found that low ego, a growth mindset, and leaning into action and high impact goes a long way here. As our next Software Engineer, Core Machine Learning you should have 4+ years of professional experience, plus: Bachelor's degree in Computer Science, Statistics, Applied Mathematics, or a related technical field, or equivalent work experience. 2+ years of software engineering experience building and maintaining production systems at consumer scale. 2+ years of hands-on experience training and deploying traditional ML models in production (e.g. classification, ranking, or regression models using PyTorch, LightGBM, or scikit-learn) Ability to work autonomously and drive initiatives across multiple product areas and communicate findings with leadership and product teams. Experience with operational, search, and key-value databases such as PostgreSQL, DynamoDB, Elasticsearch, Redis. Firm grasp of visualization tools for monitoring and logging e.g. DataDog, Grafana. Familiarity with cloud computing platforms and managed services such as AWS Kubernetes, Sagemaker, Lambda, Kinesis, S3, EC2, EKS/ECS, Apache Kafka, Flink. Professionalism around collaborating in a remote working environment and well tested, reproducible work. Exceptional documentation and communication skills. 💰Compensation For US-based applicants: $180,000 - $300,000/year + benefits + stock options The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity in the form of stock options. 🎁 Benefits Generous Holiday and Time off Policy Health Insurance options including Medical, Dental, Vision Work From Home Support Home office setup allowance Monthly allowance for cell phone and internet Care benefits Monthly allowance for wellness Annual allowance towards Childcare Lifetime benefit for family planning, such as adoption or fertility expenses Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally Monthly allowance to dogfood the app All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!). Parental Leave 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence. Please note: Whatnot will only contact you through official @whatnot.com email addresses. If you see an email impersonating a Whatnot recruiter, please disregard and report it as spam. 💛 EOE Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce. Compensation Range: $180K - $300K