Top Machine Learning Engineer Jobs in Seattle, WA

As a Machine Learning Engineer Intern, you'll enhance model performance, develop production-grade tools, and automate workflows while receiving mentorship from experienced ML professionals.

Develop and productionize a next-gen Dispatch System, build ML models, automate processes, and collaborate with various teams while mentoring other engineers.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The role involves improving Python development workflows, leading projects across teams, mentoring engineers, and enhancing developer productivity using various tools and systems.

The role involves enhancing developer tools for GM's AV engineers, addressing pain points, and mentoring team members to improve productivity and maintain quality code efficiency.

The role involves building awareness of technologies, mentoring talent, promoting a culture of engineering excellence, and collaborating on critical business issues.

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

Join the Inference team to implement features and improvements for model serving on a GPU platform, focusing on performance and reliability.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Lead technical direction on projects, mentor engineering teams, and build scheduling tools and forecasting interfaces for support agents. Collaborate with product and design teams to convert vague problems into technical solutions.

Responsibilities include designing and developing machine learning models, implementing algorithms, performing statistical analysis, and keeping up with developments in AI.

As a Staff Applied Machine Learning Engineer, you'll design and implement LLM applications, integrating ML features to enhance user experiences and scalable services.

Lead the development of generative AI services and APIs at Adobe. Architect ML workflows, optimize inference pipelines, and drive cross-functional collaboration.

As a Machine Learning Engineer, you'll develop APIs for generative models, optimize ML pipelines, and support enterprise-scale systems while collaborating with teams.

As a Senior Machine Learning Engineer, you will build and optimize pipelines, ensure model quality, and collaborate with teams to enhance fraud detection systems.

The Staff Full Stack Engineer will enhance machine learning workflows at Cruise by developing UX experiences, backend integrations, and overseeing system architecture and performance metrics.

As a Staff ML Engineer focusing on perception and computer vision at Waymo, you'll research and implement state-of-the-art models, lead algorithm development, optimize models for real-time deployment, and mentor junior engineers.

As an ML Services Engineer, you will design, deploy, and support AI-driven cloud services, optimize ML pipelines, and collaborate across teams for product development.

Lead the development of machine learning technology for Ads Ranking, improving ad delivery and user experience through collaboration with teams and product managers.

Research and optimize 3D rendering of sensor data, implement graphics algorithms, and collaborate to improve realism of simulations.

The Principal ML Engineer will develop advanced machine learning systems, mentor junior engineers, and collaborate with cross-functional teams to optimize business solutions in Merchandising and Supply Chain.

The position involves developing predictive models using machine learning techniques, collaborating with teams on product development, and optimizing algorithms for large-scale datasets.

Adobe seeks a Machine Learning Engineer for applying AI techniques to enhance customer experience through predictive models and analytics. Responsibilities include developing scalable algorithms, collaborating on product features, and solving complex business problems using statistical and machine learning methods.

Lead the development of machine learning models to enhance web security, analyze traffic, and mitigate attacks while collaborating with engineering teams.

This role involves building and supporting a scalable ML data processing platform, overseeing technical projects, and mentoring team members.