Top Remote Machine Learning Engineer Jobs in Seattle, WA

As a Fraud ML Engineer, you will ensure authentic human data is processed by building detection systems using adversarial ML techniques and managing backend systems.

As an AI/ML Architect, you will define scalable AI systems architecture, mentor teams, guide clients, and ensure ethical AI practices.

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

Build and ship ML-powered SaaS features end-to-end: design data/feature pipelines, develop and deploy models (forecasting, ranking, recommendations, optimization), define evaluation/A-B testing, monitor drift, integrate models into product workflows, influence roadmap, mentor teammates, and support MLOps and cloud data infrastructure to ensure measurable product impact.

The role involves designing, building, and deploying computer vision models for vehicle damage detection, covering the entire ML lifecycle and collaborating across teams.

The role involves developing and improving TTS/Voice Generation models, training, fine-tuning, evaluating speech models, and collaborating across research, engineering, and product teams in a fast-paced startup environment.

As a Machine Learning Engineer, you will design, build, and deploy ML models for underwriting at Stripe Capital, ensuring performance while collaborating with multiple teams.

As a Forward Deployed Machine Learning Engineer, you'll build and deploy machine learning models, enhance system performance, and collaborate with Data Science and Engineering teams for effective solutions.

The role involves building and optimizing a machine learning and simulation platform, supporting MLOps, model deployment, and infrastructure modernization, while mentoring engineers.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

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

Design, develop, and deploy production ML models and scalable pipelines. Collaborate with cross-functional teams, optimize model performance, implement MLOps deployments, monitor model health, and document experiments and metrics.

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 fine-tune and optimize LLMs for various applications, develop AI products, and enhance ML infrastructure in collaboration with cross-functional teams.

The Junior-Midlevel Developer will build and enhance Dumroo.ai's AI-powered education platform, collaborating on software components, data pipelines, and machine learning features.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

As a Senior Staff Machine Learning Engineer, you will drive AI product development, collaborate with cross-functional teams, and enhance ML models at scale.

Lead design, build, and production deployment of ML and GenAI solutions (LLMs, RAG, multi-agent systems, recommender and RL models). Architect scalable, secure inference and MLOps pipelines, mentor MLEs, collaborate with stakeholders to define roadmaps, and measure model performance and business impact. Implement fine-tuning, retrieval, orchestration, and monitoring for enterprise-grade AI products.

Design and implement scalable data pipelines and ML algorithms to optimize StackAdapt's digital advertising platform. Collaborate with teams to solve complex problems.

Build and operate ML training and serving infrastructure by designing, developing, and launching backend systems. Collaborate across teams to decompose projects, support operations and on-call, create monitoring and metrics, perform code reviews, and contribute to developer velocity and platform reliability.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

The AI/ML Engineer develops AI features for Cengage's educational products, focusing on enhancing student engagement and learning outcomes through shipping production AI capabilities.