Machine Learning Jobs in Sunnyvale, CA

The Technical Lead Manager will own the perception model for autonomous systems, leading a team to architect, train, evaluate, and deploy this model across diverse environments while reducing dependencies on traditional mapping technology.

Develop high-performance planning modules for autonomous vehicles, collaborate with customers, and apply modern software practices in a team-oriented environment.

The role involves implementing dynamic pricing models, developing ML algorithms, and maintaining infrastructure for pricing analysis and experimentation.

The Founding Product Director will define the product vision and strategy for IrisGo, lead app development, and act as a partner to OEMs, while fostering an open-source ecosystem for AI PCs.

The Senior AI/ML Capacity Engineer will develop capacity planning models, design analytical tools, and collaborate with teams to optimize costs and efficiencies.

Design, build, and operate production-grade agentic AI systems: multi-agent orchestration, retrieval-grounded reasoning, model integration, observability and governance, and production search/RAG pipelines at enterprise scale.

Design and implement production-grade VLSI/EDA tools and methodologies for multi-die package design. Build flows, applications, and automation to construct, analyze, validate, and optimize package designs to accelerate tape-out and scale engineering teams.

Lead strategic, data-driven projects to optimize operations and supply chain processes. Analyze large datasets, build statistical and ML models, create Power BI dashboards and prototypes, clean and maintain data pipelines, communicate insights to stakeholders, drive implementations, and deliver training using generative AI tools.

Administer and continuously improve the OneStream finance platform: design dimensional and cube architecture, manage business rules, integrations, security, release promotion, and production support. Partner with Finance, Accounting, IT, and external consultants to support consolidation, forecasting, reporting, SOX controls, training, and process improvement across development, test, and production environments.

Audit and improve human and model-generated data outputs for accuracy, consistency, and policy compliance. Provide actionable feedback, clarify evolving guidelines, support annotators, coach new team members, monitor workflows and blockers, identify recurring issues and edge cases, participate in calibration discussions, and document findings to improve team performance and quality at scale.

Develop and ship end-to-end machine learning models for autonomous driving behaviors across L2-L4 systems. Own data curation, training, evaluation, experimentation, and on-road validation. Improve model performance through iterative training cycles while addressing real-world safety, quality, and deployment constraints. The role may involve reinforcement learning, transformer networks, automotive systems, model compression, and embedded deployment.

Develop and deploy LLM workflows and production machine learning models for nuclear-system design and analysis. Build surrogate models for real-time digital twins, manage data pipelines, maintain rigorous information controls, and lead AI initiatives from inception through delivery. The role also involves growing a software engineering team, presenting roadmaps and demos to leadership, gathering user feedback, and collaborating with nuclear engineers in a fast-paced startup environment.

Build and scale the infrastructure layer for visual intelligence: optimize VLM inference and GPU serving, design multimodal APIs and structured outputs, ensure scalable backend systems, reliability, observability, CI/CD, and developer experience. Drive 0→1 product work with strong testing discipline, schema validation, and performance optimization.

Develop and evaluate data science modeling algorithms using sensor data, collaborate with SW engineering on data pipelines, and fine-tune algorithm performance while documenting processes.

Lead strategic positioning and integration of AI-driven and digital platforms for semiconductor process development. Define end-to-end solutions, orchestrate insight integration, partner with product and engineering, identify gaps and high-value AI use cases, and drive adoption and enablement across internal teams and customers.

The Senior Machine Learning Engineer will lead the development of a GenAI platform, enhance AI infrastructure, mentor junior engineers, and drive project ownership in a startup environment.

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.

Lead a Customer Success team, manage key semiconductor accounts, drive customer adoption, and translate technical challenges into solutions for strategic growth.

This role involves advancing autonomous vehicle simulations using Generative AI technologies, managing the lifecycle of product innovations, and collaborating in an ML engineering team.

The Machine Learning System Software Architect will lead high-performance machine learning software architecture, collaborating with teams to optimize AI solutions, evaluating architecture for performance, and driving innovation in AI training systems.

As Regional Vice President, you will drive revenue growth for Aera Technology, leading a sales team and building strategic client relationships.

Lead end-to-end product development for Assisted Autonomy, defining strategy, roadmap, KPIs, and requirements. Drive hardware and software integration, partner with Engineering, Ops, Safety and customers, manage releases and field deployments, and travel up to 25% to gather operational feedback.

Join Nuro's software team to build platform-level systems across Data Platform, Simulation, or Technical Infrastructure. Work on large-scale distributed systems, storage and compute management, microservices, CI/CD, and performance tuning to support autonomy development and simulation at scale.

Lead full lifecycle of L4 Robotaxi carline programs, build and manage a carline PM team, coordinate software/hardware/vehicle/validation integration, drive ML/data ops and in-car testing, resolve cross-functional issues, and manage customer relationships through productization to mass-production readiness.

Conduct research in machine learning and AI, focusing on robotics and AGI, while collaborating with teams and reporting findings.