Machine Learning Jobs in Sunnyvale, CA

The Senior ML/AI Engineer will enhance developer productivity for AV engineers at GM by designing, implementing scalable, reliable systems and mentoring team members.

Develop algorithms for RTL synthesis and digital logic optimization, utilizing machine learning and EDA techniques. Collaborate with design teams to implement solutions.

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.

As a Senior Machine Learning Engineer, you'll design scalable AI/ML infrastructure, optimize model training performance, and collaborate with teams to implement advanced AI solutions.

Lead and grow a team to design and deliver end-to-end AI hardware/software systems and AI GPU platforms. Define product strategy and multigeneration roadmaps, align cross-functional stakeholders, translate customer insights into requirements, ensure software enablement, and drive execution and innovation across silicon, systems, manufacturing, and go-to-market.

This role oversees cross-organizational programs, ensuring operational resilience during market expansions, and driving program outcomes through effective management and deployment strategies.

The role involves building user experiences, automating ML workflows, applying ML to data labeling, and collaborating across teams to improve data quality for autonomous vehicles.

Lead and grow a team of Technical Program Managers who run customer data projects end-to-end: staffing cadence, project setup, throughput and margin tracking, AR/billing hygiene, Airtable as system of record, onboarding TPMs, operational playbooks, and escalation for delivery risk. Serve as a player-coach partnering with Deployment Leads, FDE Manager, and GMs to ensure projects are staffed and delivered reliably.

Drive decisions on geographic expansion by building models for territory sizing and vehicle allocation, defining expansion metrics, and performing deep-dive analyses to measure and improve expansion effectiveness in partnership with product, engineering, and operations teams.

Lead ML engineering efforts for behavior planning in autonomous vehicles, develop complex models, mentor teams, and advance state-of-the-art technology.

Lead research and development of end-to-end ML models for autonomous driving, experiment with large-scale datasets and architectures, collaborate with infra and autonomy teams, optimize models for deployment, and deploy solutions to on-road vehicles.

As a new engineer at Cerebras, you'll learn their platforms, focusing on programming the Wafer Scale Engine, kernel development, and system performance modeling.

Lead the Vehicle Understanding team, managing production modules related to vehicle classification, states, and intents for Waymo's autonomous systems.

Design and implement AI-driven optimizations for software development workflows, leveraging LLMs and Agentic AI to enhance productivity and reliability.

The role involves designing and deploying strategies for congestion revenue rights, applying quantitative methods, and developing machine learning models.

Lead the Trucking Autonomy team to develop behavior systems for L4 autonomous trucks. Oversee strategy, architecture, and team management.

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

Partner with portfolio and risk managers to develop quantitative risk models, analyze U.S. power markets, improve backtesting and simulation infrastructure, attribute performance, track P&L and exposures, and deliver actionable insights to scale the trading and risk platform.

Design and build core backend services for a cloud-agnostic ML compute platform. Integrate with GPU hardware and orchestration, improve performance, scalability, reliability, and drive large cross-team initiatives to support ML training and deployment.

The Research Scientist will lead hands-on research in Conversational AI, advocate for new AI applications, mentor junior researchers, and contribute to publications.

Lead product development initiatives focused on cybersecurity, defining product requirements, collaborating with engineering teams, and driving adoption of security products.

The role involves conducting research and optimizing machine learning systems while collaborating with technical staff to enhance product performance.

As a Research Scientist Intern, you will support the technical team in developing AI product pipelines, assist with machine learning models, writing research papers, and analyze data for model improvement.

As a Research Scientist and Engineer at Collinear, you will create AI simulation environments, develop evaluation systems, and enhance real-world model performance through rigorous data-driven approaches.

Lead Collinear's research direction across evaluation, simulation, and post-training ML methods while managing a high-caliber research team. Influence customer outcomes through applied research.