Machine Learning Jobs in Bellevue, WA

Develops optimization, simulation, predictive modeling, and machine learning solutions for outbound fulfillment, transportation, routing, capacity, and supply chain operations. Translates ambiguous business problems into mathematical models, validates solutions with large datasets, conducts experiments and scenario analyses, and partners with engineering, product, and operations teams to productionize models and improve network efficiency, cost, speed, and service levels.

Design and productionize causal machine learning models, including uplift modeling and treatment-effect estimation. Analyze A/B tests and quasi-experiments, develop experimentation strategies, evaluate modeling tradeoffs, and build scalable infrastructure. Collaborate with product and engineering teams, conduct code reviews, maintain engineering standards, communicate technical insights, and mentor others.

Build privacy controls for advertising, measurement, machine-learning, and distributed systems. Conduct privacy reviews, threat modeling, and risk assessments; evaluate privacy-preserving techniques and attack risks; partner with engineering, product, legal, security, and data teams; and develop scalable privacy standards, auditing practices, tools, and documentation.

Build, optimize, validate, and deploy machine learning models for healthcare applications. Analyze healthcare data, conduct A/B experiments and statistical studies, develop scalable ML processes, research advanced AI approaches, and collaborate with software engineers on productionization. Mentor and recruit AI/ML talent, present findings to leadership, and pursue intellectual property through innovative AI research.

The Senior Product Marketing Manager will position CoreWeave's SUNK offering, develop messaging, and collaborate with engineering and sales teams to enhance product adoption and market understanding for AI training workloads.

The Lead AI Engineer will design and implement LLM-powered applications, optimize RAG pipelines, and evaluate models while integrating AI systems into production environments.

Maintains internal technical education content and coordinates recurring Lunch and Learns, engineering demos, and training sessions. Responsibilities include speaker scheduling, notes and recording publication, content audits, editorial updates, research, drafting, request tracking, and improving content discoverability. The role partners with engineers and subject matter experts to turn technical material into accessible learning resources and supports instructional design and curriculum development.

Lead technical direction and architecture for Chewy's Discovery Experience platform. Build scalable customer-facing front-end web apps and APIs, integrate search/recommendation and AI systems, ensure performance and reliability, mentor engineers, and partner across product, design, data science, and SRE.

Design, implement, and operate scalable ads delivery backend services. Own serving-time systems, collaborate with Product/ML/Infra, ensure availability and efficiency, use observability and automation, and apply AI-assisted workflows to ship production-quality code and optimize platform architecture.

Designs and delivers multi-modal technical learning programs for Sunnyvale engineering teams. Leads needs analysis, partners with senior technical stakeholders, facilitates training, owns program evaluation, and shapes technical development practice across sites.

The Director of Developer Relations leads the strategy for engaging developers around CoreWeave's AI SaaS offerings, creating content, fostering community, and improving the onboarding experience.

Define value propositions, positioning, messaging, and GTM for CoreWeave's AI researcher and developer tools. Drive product launches, sales enablement, customer advocacy, market insights, and metrics-driven measurement in close partnership with Product, Engineering, Sales, and Marketing teams.

Build and scale infrastructure management and automation solutions that detect, prioritize, and remediate vulnerabilities. Integrate security tooling, apply AI/ML for anomaly detection and predictive security, and collaborate with engineering, security, and operations teams to deliver resilient, automated vulnerability management at cloud scale.

Own the identity graph and CarrierID strategy powering audience addressability across T-Mobile’s advertising platform. Define the roadmap, evaluate identity resolution and ID-bridging approaches, partner with data science on ML methodology, query Snowflake data using SQL, and lead initiatives from prototyping through launch and iteration. Collaborate with engineering, privacy, legal, activation, and go-to-market teams to deliver measurable platform and advertiser outcomes.

Supports FP&A and enterprise analytics by developing scalable Power BI reporting, financial models, dashboards, and automated processes. Analyzes financial and operational datasets to identify trends, risks, and opportunities; improves forecasting, budgeting, and recurring reporting workflows using Excel, Python, SQL, Power Automate, and Microsoft platforms. Collaborates with finance, data engineering, IT, and business stakeholders, trains users, maintains governance standards, and contributes to the Pigment planning platform. Evaluates AI-enabled tools to improve reporting efficiency, data quality, and decision-making.

Designs software tooling, firmware, low-level drivers, and infrastructure supporting semiconductor design, verification, manufacturing, and post-silicon validation. Builds scalable EDA compute environments, validation orchestration systems, data pipelines, and hardware debugging tools. Partners with hardware and EDA teams, optimizes performance, leads architecture and code reviews, documents systems, mentors engineers, and evaluates emerging hardware platforms and toolchains.

The Staff Machine Learning Engineer will lead the development of search ranking systems, focusing on machine learning models for relevance, quality, and personalization through various advanced techniques and collaboration with cross-functional teams.

Build and operate reliable, scalable, secure infrastructure for SaaS security and Snowflake data systems. Automate infrastructure provisioning, deployments, and incident response using Terraform, Spinnaker, Kubernetes, and related tools. Ensure security and compliance, participate in on-call rotations, lead incident response and root-cause analysis, and collaborate with development, data science, and security teams on architectural decisions and service implementation.

Lead and grow the Cost Intelligence engineering team while setting technical strategy for scalable backend systems, data pipelines, APIs, and customer-facing cost optimization products. Own multi-quarter roadmaps covering cost allocation, budgeting, anomaly detection, and optimization recommendations. Partner with Product, Design, Data Science, and engineering teams to deliver reliable features, support integrations, and drive technical excellence, talent development, and end-to-end execution.

Lead technical strategy, architecture, and implementation for ML inference platform services. Design and scale distributed, high-throughput inference systems, collaborate across teams, drive availability, scalability, operational excellence, cost management, and provide company-wide technical direction and mentorship.

Design, train, and deploy ML and deep-learning models for sponsored ads: relevance, ranking, click-through prediction, auction and bidding optimization. Lead models from ideation through production, collaborate with product and engineering, set modeling standards, mentor junior scientists, and communicate results to leadership.

The Architect for Finance and Legal Systems will develop technology strategies for enterprise systems, focusing on AI, ML solutions, and data integration across finance and legal applications to enhance operational efficiency and compliance.

Lead development and production deployment of ML and deep-learning models for sponsored ads selection, relevance, ranking, CTR prediction, auction dynamics, and campaign optimization. Collaborate with product and engineering, run experiments, mentor junior scientists, deploy distributed pipelines at scale, communicate results to senior leadership, and publish research in ML/advertising venues.

Lead pre-sales engagements by presenting Snowflake to technical and executive stakeholders, delivering demos and enterprise proofs-of-concept, designing solutions, collaborating with product and engineering, and helping close large deals while maintaining deep knowledge of databases, analytics, cloud, and AI/ML technologies.

Design, build, and deploy large-scale machine learning models powering Snapchat features. Own full ML lifecycle from data analysis to production, prototype with cross-functional partners, apply modern ML techniques, and use AI tools while ensuring code correctness, security, and scalable system design.