Top Remote Machine Learning Engineer Jobs in Seattle, WA

Lead technical direction on projects, mentor engineering teams, and build scheduling tools and forecasting interfaces for support agents. Collaborate with product and design teams to convert vague problems into technical solutions.

As a Staff Applied Machine Learning Engineer, you'll design and implement LLM applications, integrating ML features to enhance user experiences and scalable services.

The Staff Full Stack Engineer will enhance machine learning workflows at Cruise by developing UX experiences, backend integrations, and overseeing system architecture and performance metrics.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

Design and deploy machine learning algorithms, develop production systems, and collaborate with stakeholders to align ML solutions with business objectives.

As a Senior Staff Software Engineer, you will design scalable infrastructure for ML models, optimize performance, and collaborate with teams to enhance ML experimentation tools.

The role involves designing, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.

Design and develop edge AI firmware for camera systems, ensuring accurate AI algorithms, collaborating on architecture, and mentoring engineers.

Design and build systems for knowledge retrieval and operational plans, optimizing information retrieval processes to support real-time decision-making.

As a Staff Machine Learning Engineer, you will lead the design, implementation, and optimization of machine learning models, collaborate cross-functionally, and drive AI strategy to enhance SailPoint's identity security solutions.

As a Machine Learning Engineer, you'll enhance ML productivity, improve model deployment, and implement algorithms for credit decisioning systems.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

Lead the development of Computer Vision and Machine Learning projects at Dandy, focusing on 3D geometric problems and automation in dental manufacturing.

The Applied Machine Learning Engineer will develop AI-driven solutions, focusing on backend systems, AI integration, model deployment, and MLOps best practices, while collaborating with cross-functional teams.

The Senior Machine Learning Engineer will develop AI workflows, collaborate with teams on models and pipelines, conduct research, mentor junior members, and innovate solutions for healthcare.

We're looking for an AI/ML Engineer to enhance our edge MLOps solutions, improve ML workflows, and support team development with strong technical expertise in Python and ML frameworks.

The Senior Machine Learning Engineer will evaluate and apply advanced ML models, integrate with company infrastructure, and support data pipeline orchestration while focusing on autonomous vehicle technology.

As a Senior Consultant II, you will integrate AI technologies into business applications, build scalable microservices, and deploy AI models in production environments.

Develop and optimize large-scale ML models and training pipelines for automating PCB layouts, collaborating on data pipeline design and novel architectures.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

Develop ML models and pipelines for autonomous tractor initiative, improving system safety and performance in production environments.

Drive and implement machine learning applications, optimize practices, formulate hypotheses, and communicate requirements to enhance advertising strategies and systems.

Lead the development of advanced recommendation systems and ML pipelines. Collaborate with cross-functional teams to enhance user engagement through optimization of machine learning models at scale.

Lead the architecture and management of AI/ML infrastructure using Kubernetes and Terraform, optimizing hybrid environments for performance and scalability.

The Machine Learning Engineer will fine-tune and deploy Large Language Models, optimize ML models, maintain data pipelines, and collaborate on AI features.