Top Machine Learning Jobs in Seattle, WA

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

The Engineering Manager, Data Science will lead a team to drive machine learning initiatives in AdTech, focusing on optimization and modeling strategies to enhance client success and operational efficiency.

Lead the design and implementation of critical Safety AI initiatives, focusing on real-time perception systems for edge devices and optimizing models for production deployment in safety-critical environments.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

Lead design, implementation, and scaling of end-to-end ML systems including feature pipelines, model training, evaluation, deployment, and monitoring. Partner with cross-functional teams to productionize models, apply MLOps best practices (automated retraining, CI/CD, drift detection), and mentor engineers to maintain high code and system quality.

Lead a team of Machine Learning Engineers and Data Scientists to design and deliver ML systems at Remitly. Collaborate across domains to implement MLOps best practices and contribute to AI strategy.

Lead design and implementation of MLOps platforms for pricing: productionize models, own end-to-end pipelines (ingest, training, deployment, monitoring), optimize data access and SQL, automate retraining and releases, improve reliability and observability, mentor engineers, and participate in on-call incident response.

Lead vision and roadmap for large-scale recommender systems across Spotlight, Discover, and Friend Stories. Technically lead engineering teams, design next‑generation recommender and retrieval architectures, incorporate SOTA research and foundation models, advance ML infrastructure for scalability and reliability, and partner cross-functionally to drive experimentation, operational excellence, and cost-effective production deployments.

Lead applied research and engineering for feedback-driven agentic AI: define reward modeling and reinforcement learning roadmap, design production learning loops and evaluation frameworks, run large-scale experiments, and ship research into production while partnering across product and engineering.

The Staff Machine Learning Engineer will lead the development of search ranking systems, focusing on machine learning models for relevance, quality, and personalization through various advanced techniques and collaboration with cross-functional teams.

Design, build, and optimize large-scale ML infrastructure: embedding generation, batch inference, data storage/compute, data management, quality systems, and production deployments with ML engineers to improve ranking and recommendation systems.

The Applied Scientist will tackle various machine learning problems, enhance valuation systems, and deploy deep learning models while collaborating with cross-functional teams.

Lead the SDL and Cash Line ML teams, developing innovative machine learning models to improve lending solutions and expand credit access. Collaborate with cross-functional teams to drive product strategy and enhance model performance, while mentoring a team of ML scientists.

As a Data Scientist, you will develop algorithms, collaborate on product requirements, and communicate data-driven insights, while enhancing product offerings and delivering actionable insights.

The Senior Manager, Machine Learning Science will lead a team focused on developing ML models for travel recommendations and ranking, optimizing the booking experience for bundled products, and mentoring ML scientists.

The role involves designing and developing a distributed ML data platform for autonomous vehicles, collaborating with stakeholders, and mentoring engineers while ensuring operational excellence.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

Lead strategy, design, and delivery of AI and digital products from ideation through scaling. Define roadmaps, integrate AI/ML and data into products, ensure data quality and governance, manage cross-functional teams, monitor KPIs, and ensure ethical, secure, and compliant deployments that drive measurable business outcomes.

Lead research and development of LLM and generative AI solutions, design scalable real-time ML models, define priorities and metrics for deep learning and RAG, promote Responsible AI best practices, and drive adoption of new methods across teams.

Design new information architectures for language models, refine their interaction with data, and develop evaluation sets to improve functionality.

The Senior Staff Machine Learning Engineer will lead innovative AI engineering projects and optimize algorithms for e-commerce applications, collaborating across teams to drive significant business impact.

Build and deploy agentic and generative AI copilot and autopilot systems for Risk and Compliance. Own end-to-end systems (data, API integrations, prompt tuning, orchestration, monitoring). Leverage payment, blockchain, graph, and unstructured data to train transformer-based models. Collaborate cross-functionally to productionize and monitor ML at scale, driving strategic roadmaps and significant business impact.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.