Machine Learning Jobs in Santa Clara, CA

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.

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

As a Senior Machine Learning Scientist, you will develop methodologies for advertising-related challenges, utilizing deep learning and statistical techniques for optimization and experimentation.

Architect and lead the development of a state-of-the-art inference platform focusing on low latency and scalability for advertising. Oversee performance optimization and collaborate with cross-functional teams.

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

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.

Lead institutional research, reporting, and business intelligence to support planning, accreditation, enrollment, and compliance. Supervise IR/analytics staff, develop dashboards and predictive analyses, manage state/federal reporting, and advise leadership using data-driven insights.

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.

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

You will design and implement high-performance backend services and machine learning pipelines for real-time AI interactions in a fast-paced environment.

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.

Drive planning and execution of multiple software and ML workstreams, manage cross-functional dependencies, gather requirements, track schedules, support development-to-deployment, and improve processes to deliver customer product releases.

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.

As a Senior Machine Learning Engineer, you will develop advanced machine learning and deep learning models and platforms for optimizing advertising performance and conduct complex experiments.

Provide strategic regulatory legal counsel for MedTech products across the device lifecycle, including premarket strategy, clinical research, approvals, launches, promotion, post-market surveillance, and quality compliance. Support regulatory interactions and inspections, supervise promotional material review, advise on fraud and abuse and privacy issues, engage in policy initiatives, partner with compliance/privacy teams, and collaborate globally within the MedTech Legal Team.

Develop and optimize lightweight machine learning models for edge AI applications, integrating into production systems and mentoring junior engineers.

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 role involves managing AI initiatives, governance, delivery, and stakeholder engagement within the AI Center of Excellence. Responsibilities include overseeing operations, strategy development, and ensuring responsible AI practices.

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