Machine Learning Jobs in Bellevue, WA

As an Applied Scientist, you will develop ML and deep learning models for forecasting in advertising campaigns, collaborate with engineers and product teams, and continually improve model performance based on data-driven insights.

Lead pre-sales efforts for Media & Entertainment customers: present Snowflake to executives and technical audiences, deliver demos and POCs, design solutions, collaborate with product and engineering, and close large deals while maintaining deep industry and competitive knowledge.

The Project Support Coordinator will assist in data collection for AI and ML, guide participants, manage equipment, and respond to project updates.

Join the Inference team to implement features and improvements for model serving on a GPU platform, focusing on performance and reliability.

The role involves designing and developing a distributed ML data platform for autonomous vehicles, collaborating with stakeholders, and mentoring engineers while ensuring operational excellence.

Lead fraud mitigation strategy and operational excellence for financial services programs. Manage technical integrations, compliance, SOX controls, vendor engagements, audits, and cross-functional delivery. Design and implement fraud detection/prevention, deploy ML/AI-driven controls, analyze fraud performance, build SQL/Tableau dashboards, and ensure readiness for peak retail and digital transaction periods. Hybrid role based in Bellevue, WA.

Lead research and development of LLM and generative AI solutions, design scalable real-time ML models, define priorities and metrics for deep learning and RAG, promote Responsible AI best practices, and drive adoption of new methods across teams.

As an Enterprise Account Executive at Salesforce, you will drive revenue growth by leveraging AI-driven solutions, understanding client needs, and demonstrating how Agentforce can solve business challenges while fostering client relationships.

The Senior Product Manager will lead the development of The Trade Desk's infrastructure, focusing on scalability, security, and optimizing complex systems to support high-performance workloads. Responsibilities include modernizing core systems and collaborating with cross-functional teams to enhance product capabilities and performance.

Lead credit analytics for the Send Now Pay Later product: build and maintain credit policies, pricing models, vintage and NPV analyses, executive reporting, model integration and testing, and explore alternative data to optimize approval rates and portfolio health.

Lead credit analytics for the Send Now Pay Later product: build and optimize valuation, vintage and NPV models; manage credit policies, portfolio monitoring, and NPL reporting; integrate and test scoring models with engineering/data science; and research alternative data to improve predictive performance.

Lead quantitative credit analytics for a Send Now Pay Later (SNPL) product: build and maintain credit policies, pricing and NPV models, vintage analysis, portfolio monitoring, model integration/testing, and alternative data evaluation to optimize approval rates and manage portfolio health.

Lead research and development of AI/ML-driven threat detection: analyze large datasets, build and validate proofs-of-concept, collaborate with threat and engineering teams, and help productionize scalable security detection systems.

Design and build scalable, distributed server/cloud systems using C/C++ and C#/Java; apply ML, data/process modeling, and automation to optimize logistics and resource allocation. Collaborate in large teams, debug complex systems, and adapt quickly to new technologies.

The Director of Design Technology leads the technical design practice, shaping tools, systems, and AI capabilities that empower the UX team for scalable product experiences.

As a Senior Technical Program Manager, you will oversee resource management, strategic forecasting, and technical problem-solving for Waymo's compute and storage infrastructure, ensuring cost-efficiency and effective resource allocation.

The Staff Technical Program Manager will manage simulation compute resources, develop execution strategies, and influence stakeholders for project success.

Design, build, and evaluate next-generation ranking and recommendation models using LLMs, RLHF, and preference learning. Develop user understanding systems for conversion and value estimation at massive scale. Apply reinforcement learning and optimization to bidding and auction dynamics. Design and run causal inference and A/B experiments. Partner with engineering to productionize models and communicate results to technical and non-technical stakeholders.

The Staff Research Scientist will define research directions in AI and LLMs, develop models and systems for autonomous decision-making, and lead efforts to translate research into impactful solutions while mentoring team members.

Design and operate large-scale data pipelines for ML training, integrating orchestration tools, optimizing performance, and leading architectural improvements.

As a Senior Software Engineer, you will design and implement AI/ML tools for game development, collaborating with cross-disciplinary teams to enhance workflows and player experience.

The role involves building and maintaining machine learning infrastructure, including data pipelines and distributed training workflows, while collaborating with ML engineers to enhance efficiency and reliability.

As a Senior Machine Learning Infrastructure Engineer, you'll design and maintain the infrastructure for ML models, ensuring reliable performance and optimizing serving pipelines in a high-scale environment.

The Machine Learning Engineer will implement and evaluate ML algorithms, focusing on model development, A/B testing, and cross-functional collaboration to drive innovative solutions for financial challenges.

Define and lead modeling architecture for personalization, matchmaking, recommendations, and social discovery. Build large-scale real-time inference systems, develop models for skill, behavior, trust & safety, and multi-objective optimization. Drive Responsible AI, experimentation, observability, and cross-functional standards while mentoring senior engineers and influencing ML strategy.