Top Machine Learning Jobs in Seattle, WA

As a Machine Learning Engineer, you will lead end-to-end ML projects, integrate solutions, and collaborate with cross-functional teams to drive data science solutions that align with business objectives.

Design and implement ML solutions, fine-tune and integrate LLMs, and collaborate on deploying intelligent features in production environments.

As a Software Engineer Intern, you will build features for user-facing products, design data pipelines, implement scalable services, and contribute to technical documentation while being part of a collaborative team.

Responsible for building and maintaining software that interfaces with networks, requiring expertise in network protocols, OS programming, and debugging distributed systems.

Machine Learning Systems Engineers will develop end-to-end 3D machine learning systems, optimize training pipelines, and improve model performance within a collaborative team.

Lead the design and execution of ML-based targeting products, improving advertiser outcomes while mentoring junior engineers and collaborating with cross-functional partners.

The role involves designing and scaling ML infrastructure for LLMs, including building training pipelines and deploying models in cloud and on-prem environments. Collaboration with engineers and managing GPU/TPU workloads is key.

The Software Engineer will develop machine learning infrastructure, optimize models, and create tools for data analysis while collaborating with a diverse team.

As a Senior ML Training Engineer, you will architect and implement distributed training solutions, optimize multi-GPU setups, and support customer training workflows in AI infrastructure.

The Machine Learning Engineer III will design, develop, and deploy machine learning models and algorithms, mentor junior staff, and collaborate with cross-functional teams to solve complex business problems.

The role involves designing and maintaining ML infrastructure, ensuring performance and security, collaborating with ML engineers, and implementing modern AI capabilities.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

Design and implement backend ML systems for personalized feeds at Reddit. Mentor teams, drive technical discussions, and improve MLOps tools.

Lead high-impact machine learning projects, developing systems for advertising optimization, collaborating cross-functionally, and implementing statistical techniques.

The role involves developing cloud solutions and enhancing ML/AI pipelines, ensuring service availability, and automating deployments in a scalable environment.

Develop and optimize 3D rendering algorithms for sensor simulation using cutting-edge graphics and GenAI/ML techniques, collaborating with various teams to enhance data fidelity.

Lead the integration of AI in CPU/SoC design and verification. Build AI copilots for workflows, partner with EDA vendors, and define methodologies for CPU design improvement.

As a Senior Machine Learning Engineer, you will build and productionize ML models, develop scalable infrastructure, and mentor teams to optimize marketing products.

The Software Engineer (Full Stack) will develop and deploy clinical AI/ML products, ensuring product quality and collaborating with cross-functional teams.

As a Lead Machine Learning Engineer, design and maintain scalable ML solutions, optimize workflows, evaluate model performance, and collaborate with cross-functional teams to integrate complex data-driven applications, ensuring high reliability and performance standards.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

As a Senior Python Engineer at ClickHouse, you will enhance the Python ecosystem for data scientists and ML teams, ensuring efficient data integration and optimizing workflows within the open-source environment.

The role involves designing and implementing cloud-native infrastructure for AI/ML workloads, optimizing Kubernetes environments, and contributing to open-source MLOps tooling.

Research and optimize 3D rendering of sensor data, implement graphics algorithms, and collaborate to improve realism of simulations.

The Staff Software Engineer will architect, implement, and maintain foundational ML infrastructure and feature stores for Reddit, collaborating across teams to advance ML capabilities.