Top Machine Learning Engineer Jobs in Seattle, WA

The Staff Machine Learning Engineer will develop machine learning models to enhance advertising strategies, improving relevance, ranking and customer engagement for Chewy's sponsored ads.

As a Staff Machine Learning Engineer, you'll enhance credit products through advanced modeling techniques, data analysis, and ML operations, supporting robust decision-making processes.

Design, implement, and manage complex machine learning algorithms with a focus on computer vision. Experience in MLOps, cloud platforms, and testing AI technologies is essential.

The role involves deploying machine learning to enhance Chewy's advertising solutions, developing models for product ranking and prediction, and collaborating with product leaders. Responsibilities include leading new models, publishing research, mentoring, and driving technical strategies.

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

Lead the machine learning strategy, design scalable ML systems, drive MLOps, mentor engineers, and comply with AI governance.

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.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

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.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

Develop and expand revenue forecasting and dynamic pricing systems, design models to predict demand, optimize pricing strategies and ensure data quality.

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.

Lead the design and deployment of machine learning models for personalized navigation and recommendations, managing projects end-to-end with a focus on user-centric solutions.

Design and deploy ML models for fraud detection, develop data pipelines, partner with teams to ensure effective fraud prevention, and enhance detection accuracy.

Lead the design, development, and deployment of foundational ML systems, influence architecture, mentor engineers, and drive strategic initiatives within SailPoint's AI team.

The Machine Learning Engineer will develop and improve ML models for product surfaces, build data processing pipelines, and leverage machine learning technologies in advertisements.

As a Senior Machine Learning Engineer, you will design and build ML models for patient-provider matching, focusing on personalization and ranking. Responsibilities include model development, A/B testing, and collaborating across teams to improve patient experiences.

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

As a Senior Full-Stack Engineer II at DigitalOcean, you'll lead and build AI application services, collaborating on design and operational excellence while maintaining APIs and working with ML platforms.

As a Senior Machine Learning Engineer, you will build scalable ML systems, lead the ML lifecycle, mentor engineers, and collaborate across teams.

Design and build core ML systems for AI agents, managing the lifecycle from problem framing to deployment, ensuring solutions are scalable and enterprise-ready.

The Machine Learning Engineer will lead the design and integration of predictive models for monetization, retention, and user engagement, ensuring ML systems operate reliably at scale. Responsibilities include model development, collaboration with engineering teams, and embedding models into products.

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