Top Machine Learning Engineer 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.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

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 Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

The Senior Software Engineer will provide technical leadership, build and scale AI/ML systems, maintain APIs, and collaborate on design while independently shipping product features.

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

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

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

The Senior Machine Learning Engineer at Chewy will develop and deploy ML models for sponsored ads, collaborating across teams to optimize advertising strategies. Responsibilities include model ideation, experimentation, and mentoring junior scientists while communicating insights to leadership.

The role involves developing machine learning models for sponsored ads, improving selection and ranking, and collaborating with product teams to optimize advertising solutions.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

Design and build Go backend services on AWS to support scalable AI/ML workloads. Develop core platform components (feature store, orchestration, model serving), deploy GenAI apps, optimize infrastructure and CI/CD, and collaborate with data scientists, ML engineers, and product teams to deliver end-to-end ML solutions.

Partner with CV researchers to productionize models, optimize training and real-time inference performance, design reusable abstractions, and collaborate with MLOps/backend teams to evolve the CV inference platform for scale and reliability.

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

Define and lead modeling architecture for personalization, matchmaking, recommendations, and social discovery. Build large-scale real-time inference systems, develop models for skill, behavior, trust & safety, and multi-objective optimization. Drive Responsible AI, experimentation, observability, and cross-functional standards while mentoring senior engineers and influencing ML strategy.

Build and own full-stack UX and backend systems for the ML lifecycle: design architecture, integrations, observability, CI/CD, and production frontend/backends. Lead technical initiatives, mentor engineers, and collaborate across teams to scale ML platform capabilities.

The Machine Learning Engineer will build and maintain ETL pipelines for image datasets, develop model training infrastructure, and work closely with farmers to implement ML solutions.

Develop machine learning solutions and integrate state-of-the-art LLM/VLM models into Waymo's production environments, collaborating with perception and planning teams.

The role involves leading machine learning initiatives to enhance automated testing for autonomous vehicles, improve model interpretability, and collaborate with cross-functional teams.

The Machine Learning Engineer will design, deploy, and maintain ML models, work with large datasets, and collaborate with teams to enhance AI solutions.

The Staff Machine Learning Engineer will design, code, and deploy ML models, improve backend systems, and mentor engineers.

As a Principal Machine Learning Engineer, you'll develop advanced ML solutions using LLMs and Knowledge Graphs, leading teams and driving innovation in AI technologies for improved customer experiences.

The role involves designing, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.

Lead the architecture and implementation of a scalable AI/ML platform, focusing on data pipelines and integration of ML capabilities in business systems. Mentor and collaborate with cross-functional teams to optimize performance and deliver business value.