Top Machine Learning Jobs in Seattle, WA

Lead architectural vision and development of scalable infrastructure for self-driving technology, mentoring engineers and overseeing complex projects.

Design and build ML infrastructure components for autonomous vehicles, ensuring scalability and robustness for high-volume data processing and model training.

Work with the product team on automating data ETL pipelines, deploying ML models, and connecting ML models to user interfaces. Collaborate with cross-functional teams on product development.

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.

Lead the development of cutting-edge AI services and platforms for machine learning, ensuring operational readiness and driving innovation in ML workflows.

Lead the design and implementation of GPU compute clusters for AI and HPC workloads, managing infrastructure and optimizing performance.

As an ML Solutions Architect, design, implement, and lead machine learning solutions for Conversation AI, collaborating with cross-functional teams to address complex business challenges.

Design and maintain scalable data pipelines, develop infrastructure for dataset reliability, implement benchmarking systems, and automate quality checks for ML models.

The role involves designing and implementing distributed systems for batch inference workloads, creating developer-friendly APIs, and fostering engineering excellence.

As a Machine Learning Scientist, develop ML models focusing on NLP, Speech, and Computer Vision while working on various aspects of the ML stack.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

The Senior Software Engineer will own large-scale data mining workflows, improve ML products through high-quality datasets, and analyze model performance across driving scenarios.

The Director of Engineering, Data & AI/ML will lead Bolt's data initiatives, manage teams, drive technical vision, and collaborate across functions to enhance e-commerce experiences.

The Machine Learning Engineer will enhance search retrieval, train ranking models, build query understanding systems, and ensure robust pipelines for Reddit's AI-driven products.

As a ML Engineer focused on inference, you'll design and optimize deep learning models for real-time communication AI applications, collaborating with cross-functional teams and ensuring production readiness.

Design and maintain scalable machine learning infrastructure, collaborating with data scientists, ensuring performance, security, and compliance of AI systems.

As a Software Engineer, you'll enhance the user experience of ML tools, optimize workflows, and collaborate with product managers on ML infrastructure projects.

Develop and implement ML models for search and recommendations, focusing on generative AI technologies and multimodal processing to improve creative experiences.

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

Join the Snowflake team to design, implement, and optimize machine learning systems that impact developer productivity and platform efficiency. Collaborate with diverse teams on ML tools and infrastructure while enhancing software engineering practices.

Lead the backend engineering team for Runway's machine learning platform, focusing on building infrastructure, monitoring, and scaling production processes.

The Engineering Manager - Data & ML will redesign and scale Underdog's data and ML platform, establishing best practices, leading a team, and collaborating with cross-functional teams to optimize data systems.

Lead the development of AI agents and infrastructure, collaborate with stakeholders, design APIs and SDKs, and advocate for best practices.

The Senior Software Engineer will develop and maintain foundational ML infrastructure for feature computing, storage, and retrieval, impacting numerous teams at Reddit.