Machine Learning Jobs in San Jose, CA

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.

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.

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.

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.

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.

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.

The role involves building and leading teams to optimize ads auction systems, partnering with various teams to define strategies, and conducting experiments for optimization.

Interns will work on machine learning solutions for autonomous driving, contributing to real-world projects in perception, prediction, and planning.

The Software Intern at Cadence will work on research and development using machine learning technologies for on-chip parasitic modeling in a team environment.

Design and develop Multi-Physics System Analysis software, debug errors, implement features, and write tests.

Lead the design, development, and deployment of AI software components while partnering with engineers and scientists to deliver innovative AI solutions at Capital One.

The Senior Solutions Architect will develop and deploy AI infrastructure solutions, work with customers, and drive technical pre-sales activities.

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

Lead cross-functional finance AI and data projects: translate finance processes into technical solutions, manage stakeholders and requirements, track multiple projects to delivery, understand AI/ML and data architectures, and drive decisions while ensuring projects meet business and technical objectives.

Lead roadmap and execution for ad-serving, bidding, targeting, auction mechanics, and core marketplace infrastructure. Apply AI/ML and generative models to improve ROAS, budget utilization, and advertiser outcomes, partnering with engineering, analytics, commercial, finance, and legal. Drive experimentation, A/B testing, and data-driven product decisions.

Lead business development for assigned product lines across the Americas, driving new and renewal revenue. Develop pipeline, articulate value propositions, run demos/PoCs, collaborate with sales, engineering, product and marketing, and build long-term customer relationships. Support forecasting, proposals, events, and capture customer feedback for product evolution.