Top Senior Machine Learning Jobs in Seattle, WA

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

As a Senior Machine Learning Engineer, you will design and implement systems for ML and NLP, optimizing models and tools for Clover's healthcare solutions.

The Senior Machine Learning Researcher will design experiments, research new algorithms, and collaborate on deploying models for computer vision and robotics applications.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

As a Senior Applied ML Scientist, you'll develop fraud detection models, research new fraud types, and write production code while collaborating across teams to enhance SentiLink's identity verification solutions.

As a Senior Machine Learning Engineer, you'll design and implement large-scale ML systems to enhance ad relevance and performance, mentor engineers, and collaborate with cross-functional teams in Mandarin.

The Senior Machine Learning Engineer will design, deploy, and operate ML systems for advertising, collaborating with cross-functional teams to enhance performance and reliability. Responsibilities include mentoring, promoting best practices, and owning ML project lifecycles.

The Senior Machine Learning Scientist will lead the development of ML systems for personalized CRM marketing, define technical roadmaps, and mentor team members while collaborating with cross-functional teams.

As a Senior Machine Learning Engineer, you will develop and deploy machine learning models, conduct research, and collaborate on data solutions.

The Founding ML Engineer will develop and deploy ML systems, collaborate with teams, and translate ambiguous problems into production ML solutions, shifting between client delivery and platform development.

Lead the design and production of ML systems for Pinterest's ads measurement products. Collaborate with various teams to improve measurement quality and contribute to technical direction and best practices.

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

Lead ML projects, guiding technical direction and platform capabilities. Collaborate across teams to deliver production ML systems impacting customers. Advocate for AI-first tools and mentor engineers.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

The Machine Learning Researcher will design datasets and evaluate environments for agentic systems, focusing on data quality and benchmarking model performance in RL settings. They will collaborate with teams to translate workflows into evaluative frameworks and improve the understanding of high-quality datasets.

The role involves developing machine learning algorithms to enhance customer experience. Responsibilities include end-to-end ML lifecycle management, validating models, and collaborating with teams to address complex problems.

Lead a team of machine learning engineers and data scientists to develop algorithms for personalized shopping, enhancing client engagement and driving growth through AI and data science.

Lead end-to-end ML projects for fraud detection: develop, deploy, monitor, and iterate production models and experimentation frameworks. Improve model performance, build scalable ML pipelines, collaborate with Product/Engineering/Risk, and champion testing, documentation, and model-monitoring best practices to ensure robust, high-impact solutions.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

The ML Engineer will design and implement AI solutions for Axon's devices, collaborating with scientists to enhance model efficiency and ensure responsible AI deployment.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

The Principal Machine Learning Engineer will design and scale ML systems for personalization and search, mentor engineers, and lead major ML initiatives at Fetch.

Design and deploy production recommendation and retrieval engines, build data orchestration pipelines for multiple modalities, implement agentic workflow frameworks, and prototype, optimize, and scale models with monitoring, governance, and low-latency SLAs.