Top Machine Learning Engineer Jobs in Seattle, WA

Lead end-to-end AI/ML projects: research, prototype, optimize, and productionize ML and LLM solutions for healthcare. Mentor and recruit teams, run experiments and A/B tests, present results to leadership, and pursue AI research and IP.

Lead the technical roadmap for the Ad Marketplace, design and optimize machine learning models, and collaborate with teams to meet objectives.

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.

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.

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.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

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

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

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 Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising 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.

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.

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.

This role involves developing AI applications, focusing on LLMs and agent frameworks, and requires research skills in ML with experience in data strategy.

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.

The role involves technical leadership, building AI/ML services, maintaining APIs, and leading cross-functional projects to deliver scalable solutions.

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.

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.

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

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 Applied Machine Learning Engineer will develop machine learning models, transform data science prototypes, and build efficient self-learning applications for greenhouse operations.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.