Machine Learning Jobs in Sunnyvale, CA

As a Software Engineer intern, you'll work on AI-driven projects spanning data management, onboard systems, ML infrastructure, simulations, and technical infrastructure, collaborating with experts in various fields.

Looking for new graduate software engineers to work in areas like Data Platform, Onboard Systems, or Technical Infrastructure focusing on AI and autonomy technologies.

Lead reliability engineering for 2.5D/3D advanced semiconductor packages: perform physics-of-failure modeling, define and execute stress tests, manage OSAT qualifications, select and qualify materials, perform failure analysis (FIB/SEM/TEM/X-ray), drive root-cause and corrective actions, and collaborate with design, process, and suppliers to improve package reliability and manufacturability.

The Demand Planner is responsible for improving forecast accuracy, analyzing market trends, and collaborating across functions to support supply chain effectiveness and strategic decision-making.

Lead modeling of weather patterns and their impact on the Waymo Driver. Build pipelines and spatio-temporal models integrating multiple weather data sources. Measure performance in adverse weather, develop scalable analysis frameworks, optimize operational mitigation processes, and collaborate with product and engineering. Act as a technical contributor and lead, scope ambiguous problems, and champion measurement rigor across teams.

Lead technical vision and architecture for ML-driven trajectory generation in autonomous vehicles. Build and deploy scalable training pipelines, integrate models into real-time safety-critical onboard systems, mentor senior engineers, drive cross-functional initiatives, and move solutions from research to production using simulation and large-scale datasets.

Lead design and deployment of production-grade ML systems (ranking, retrieval, LLMs). Drive architecture decisions, run experiments and evaluations, build scalable feature pipelines and monitoring, mentor engineers, and collaborate cross-functionally to integrate AI into products and scale ML capabilities.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, identity abuse, merchant/marketplace risk, scams, and other adversarial activity. Own end-to-end production lifecycle: data contracts, low-latency inference, batch scoring, feature quality, deployment, monitoring, incident response, rollback, and feedback loops. Develop AI-assisted workflows and reusable decision capabilities while partnering with modelers, product, compliance, and operations.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

You will own the compilation stack transforming AI models into optimized inference for autonomous driving. This includes developing tools and techniques for model export and optimizing performance while ensuring safety and reliability.

The role involves designing and building production systems for AI agents, implementing algorithms, mentoring engineers, and collaborating with experts on enhancing AI products.

The role involves developing quantization and compression strategies for AV models, conducting numerical sensitivity analyses, and creating automated tooling for low-precision deployments, emphasizing safety and performance.

Lead the design and advancement of AI platform infrastructure, focusing on distributed training, efficiency, and optimization of ML models. Collaborate with teams and guide architectural decisions.

The Senior Compiler Engineer will develop a model compilation toolchain for deploying optimized machine learning models in autonomous vehicles, focusing on performance engineering and collaboration with cross-functional teams.

Develop and evaluate ML and perception models for future sensing and autonomous driving. Work on detection, tracking, classification, sensor fusion, training pipelines, validation, robustness metrics, and integrate models into onboard systems while collaborating with cross-functional teams.

Lead end-to-end ML and perception efforts for future sensing in autonomous vehicles: design sensor architectures, multi-modal fusion, model development, metrics, simulation-driven evaluation, system integration, and production readiness while mentoring engineers and building scalable data and training infrastructure.

Lead development and production of underwriting and credit decisioning models across Cash App Borrow and Afterpay. Own full modeling lifecycle: problem formulation, feature engineering, training, calibration, experimentation, deployment, monitoring, and iteration. Build decision frameworks, agentic engineering workflows, and collaborate with cross-functional partners to align model behavior with business and regulatory goals.

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

The AI Enterprise Engineer will work with enterprise customers to define model specifications, analyze agent behavior, and benchmark models using Bespoke Labs tools, requiring a strong foundation in AI/ML and production deployment.

The Solutions Engineer will engage with stakeholders to design AI-powered engineering solutions, bridging business needs and technical execution while guiding customers through AI integration.

Lead design, build, and operate scalable observability systems for distributed cloud and on-vehicle environments. Contribute code and reviews, create technical designs, build tooling to collect observability signals, run PoCs for new tools, partner with engineering teams, define SLIs/SLOs, guide roadmap decisions, and mentor engineers to improve developer productivity and reliability.

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

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.

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.