Machine Learning Jobs in Sunnyvale, CA

Design and scale real-time bidding systems, auction mechanisms, bid forecasting, pacing algorithms, and marketplace intelligence models. Apply machine learning, reinforcement learning, control theory, experimentation, and large-scale data analysis to optimize advertiser returns. Lead projects from architecture through offline evaluation and online A/B testing, collaborating with product, infrastructure, and engineering teams to deliver measurable business impact.

Lead product strategy and execution for ML training workflows and platforms. Own roadmap, define requirements, measure KPIs for developer productivity, training reliability, experiment management, and cost. Partner with engineering, infrastructure, data, finance, and autonomy teams to prioritize investments, reduce cycle time, and deliver scalable tooling. Mentor product peers and communicate tradeoffs and metrics to senior leaders.

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.

Develop optimized GPU algorithms and high-performance machine learning solutions for vector search, databases, and data processing. Responsibilities include designing, implementing, benchmarking, debugging, and optimizing C++, CUDA, and Python libraries; developing clustering and visualization algorithms; collaborating cross-functionally; and contributing to open-source projects such as cuML, cuVS, and RAFT.

Develop and productionize online mapping machine learning models and algorithms for autonomous vehicles. Analyze system performance, improve data, architectures, and evaluation, build training pipelines, and integrate models with centralized autonomy systems. Collaborate with autonomy, infrastructure, and systems teams to deliver robust mapping solutions using camera and LiDAR data in uncertain environments.

Lead and grow a Product Data Science team to drive modeling, experiments, and data analysis that improve Waymo Driver performance and operational efficiency. Partner with senior leadership and cross-functional teams to prioritize resources, support geographic expansion, and translate vehicle and operational data into scalable product decisions.

Design and deploy machine learning models for creating HD maps, utilizing advanced ML techniques and collaborating with other teams to deliver reliable solutions.

The Founding ML Research Engineer will design and evaluate ML models, develop experimentation pipelines, and contribute to AI research while optimizing training processes.

The Founding ML Engineer will build and scale machine learning systems, focusing on ML pipelines, model implementation, and collaboration with teams to drive measurable impact.

Design and lead large-scale machine learning and backend systems for advertiser growth, including budget pacing algorithms, GenAI creative generation infrastructure, marketplace experimentation, high-throughput billing pipelines, and real-time stream processing. Analyze marketplace and financial data, optimize advertiser performance, ensure billing accuracy and fault tolerance, lead multi-quarter technical roadmaps, and mentor senior engineers.

The Senior AI/ML Engineer will enhance developer productivity by improving Python workflows, leading projects, mentoring engineers, and driving best practices.

Lead applied research to advance continuous learning for agents: design and evaluate LLM post‑training and RL methods, implement and deploy experiments at scale, validate research on customer tasks, optimize GPU/distributed training, and mentor engineers while driving cross‑functional technical direction.

Drive applied research to enable continuous learning for agents: design and evaluate LLM post-training methods (fine-tuning, RL, distillation), run large-scale GPU experiments, validate approaches on customer tasks, and help deploy and scale models and infrastructure across the stack.

Analyze and reduce RTL and pre‑silicon power for GPUs and networking chips using EDA tools and AI/ML. Run workloads, perform comparative power analysis, prototype Verilog features, debug power anomalies, and collaborate with architects, RTL designers, and physical design teams to drive power improvements.

Design, implement, and evaluate perception algorithms and 4D world representations for autonomous vehicles. Train and deploy ML and computer vision models from data collection to production, test on real vehicles, and collaborate with data, behavior, and research teams to deliver production-ready autonomy software.

Design and implement low-speed motion planning and control modules for autonomous vehicles, characterize vehicle dynamics to close sim-to-real gaps, evaluate academic research, and build optimal-control solutions (e.g., nonlinear MPC, MPPI) deployable on production vehicle platforms.

Design and ship deterministic, safety-critical classical or ML motion planners for fallback and minimal-risk maneuvers. Build planners for degraded perception and partial observability, evaluate behavior at scale using simulation and real-world data, develop metrics and analysis tools, and collaborate with perception, prediction, controls, safety, and remote assistance teams to deliver a reusable fallback platform.

Lead development and deployment of high-performance motion planning modules for autonomous vehicles. Mentor engineers, set technical direction, integrate perception, prediction, and lightweight maps, optimize performance, establish testing/validation for production hardware, and manage customer engineering relationships to align deliverables with autonomy goals.

Lead and grow an engineering team building scalable behavior systems for L2/L4 autonomous vehicles. Own architecture and delivery of safety-critical behavior planning across diverse driving domains, collaborate with Perception, Research, Simulation, and Vehicle Operations, mentor engineers, and drive technical and business decisions for production autonomy systems.

Design and execute validation strategies for autonomy modules (perception, planning, prediction, localization) for L4 trucking. Build datasets from simulation and real-world data, develop ML/statistical models and pipelines to measure safety performance, produce metrics, safety cases, and release recommendations.

Develop high-performance motion planning modules for onroad autonomous vehicles, integrating lightweight maps and perception outputs. Ship production C++ code, deploy to vehicle hardware, test on road, and collaborate with customers to meet diverse operational design domains.

Develop real-time intraoperative ML and computer vision software for robotic-assisted minimally invasive surgery. Design, prototype, implement, test, and deploy algorithms and user-facing components, support system integration, produce documentation and patents, and iterate from clinical feedback to deliver production-ready code.

Develop and execute automated software tests and test protocols for a robotic surgical platform; contribute to CI/CD pipelines, test plans, reliability verification, data analysis, issue logging, cross-functional debugging, and generate dashboards and executive summaries.

Develop and implement large-scale machine learning and foundation-model systems, collaborate with research teams to integrate technologies, maintain ML lifecycle (data preprocessing, pre-/post-training, evaluation), conduct design reviews and code reviews, debug system issues, contribute to documentation and research publications, and represent the institute at conferences.

Lead strategic GTM and co-selling initiatives with Google Cloud to drive NVIDIA AI adoption. Develop and maintain technical enablement assets, run developer activations and events, collaborate with Google Cloud field and engineering teams, convert samples into demos and labs, and translate customer feedback into product and roadmap insights.