Top Machine Learning Engineer Jobs in Seattle, WA

Lead modeling strategies for AI Bots in League of Legends by developing and implementing ML systems, collaborating with teams, and ensuring player experience enhancement through advanced ML methods.

Develop AI-powered solutions for personalized content and marketing. Collaborate with teams to optimize ML models and pipelines at scale, mentoring engineers and driving strategic growth initiatives.

The Machine Learning Engineer will design and implement AI/ML projects on AWS, optimize data architectures, and ensure secure data management.

The Machine Learning Engineer will design and deploy computer vision models, build training pipelines, and enhance ML infrastructure to improve agricultural field operations.

Design and implement scalable machine learning pipelines, collaborate with cross-functional teams, ensure deployment standards, and champion best practices in observability and monitoring.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

Design, architect, and deploy generative AI/LLM solutions from prototype to production; work directly with clients to translate business needs into technical plans; write production-quality code integrating LLMs and ML models; collaborate with cloud, DevOps, and frontend teams; support proposals, sales, and evaluation/observability of models.

As a Machine Learning Engineer, you'll create and optimize production-ready ML solutions, manage the ML lifecycle, and conduct experiments.

As a Senior Machine Learning Engineer, you'll design and manage ML infrastructure, work with Data Science to implement models, and oversee system health and reliability.

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

As a Principal Machine Learning Engineer, you will architect AI solutions, collaborate with scientists, and optimize models for edge deployment. Your work enhances public safety applications.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

Develop and maintain scalable AI/ML architectures, collaborate on integrating solutions into products, and ensure compliance with industry standards.

In this role, you'll develop machine-learning models for geospatial data, leveraging EO, MSI, and SAR sensors, and oversee model lifecycle from development to deployment.

The Staff Machine Learning Engineer will develop ML platforms, design predictive models, and automate workflows for improved decision-making and user experience at GEICO.

Develop and train models for sensor-level scenario generation using deep learning and multi-sensor fusion for autonomous vehicle perception at Zoox.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

Lead technical direction and execution of Lime's CX automation platform, building scalable backend services, decision engines, and human-in-the-loop workflows to automate rider issue resolution while enforcing fraud and trust guardrails and improving operational metrics.

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

Design, build, and maintain scalable AI/ML architectures; collaborate with data scientists, engineers, product, and compliance to integrate models; evaluate tools and processes; monitor performance and ensure industry-standard compliance and ethical practices.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

The Senior Data Engineer will develop and deploy machine learning models, build end-to-end ML pipelines, optimize performance, and collaborate across teams to enhance AI capabilities at ClickUp.

The Senior AI/ML Engineer will design, build, and deploy Generative AI and ML platforms, ensuring compliance and high performance. Responsibilities include developing foundational services, overseeing model training infrastructure, and mentoring junior engineers.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.