Machine Learning Jobs in San Jose, CA

Develop and deploy EDA/CAD software, automation, and AI-assisted tools to accelerate custom memory IC design workflows. Collaborate with design, layout, verification, and CAD teams to integrate LLMs, generative AI, and automation into verification, modeling, and tape-out flows.

Design and implement digital ASIC logic across the full ASIC lifecycle: specifications, microarchitecture, RTL (SystemVerilog), simulation, synthesis, static timing analysis, timing closure, linting, CDC, and top-level integration. Leverage GenAI and agentic tools, collaborate cross-functionally, and support interfaces such as PCIe, NVMe, DRAM, NAND, and AXI.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Lead development and implementation of advanced AI/ML solutions, design and optimize models and algorithms, transform raw data into actionable insights, manage projects end-to-end, supervise and mentor teams, maintain quality and standards, and manage client engagements and expectations.

As a Senior Machine Learning Scientist, you will develop advanced machine learning models for personalization, collaborate with cross-functional teams, and mentor junior scientists, ensuring impactful solutions in production scenarios.

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

As a Staff Machine Learning Engineer, you will enhance credit modeling, manage full credit modeling stacks, and support innovations within regulated banking frameworks.

Lead and own the design direction for Expedia Group's AI-powered search experiences. Drive vision, high-fidelity design, prototyping with LLMs, systems thinking, and cross-functional partnership to translate ML into intuitive, scalable search and discovery experiences while mentoring designers and establishing design standards across brands.

Lead design and deployment of enterprise-scale multi-agent AI systems across the semiconductor lifecycle. Define strategy, architect agentic AI platforms (LLMs, RAG, knowledge graphs), identify automation opportunities, establish AI governance, integrate with EDA and operations systems, mentor technical leaders, and represent the company externally.

Ten-week, full-time paid Data Science internship for current PhD students. Interns will build and evaluate modeling and analytics tools, integrate internal and external data sources, design data science models, and communicate results. Candidates must continue their PhD after the internship and may be evaluated for full-time roles upon graduation.

Ten-week, full-time paid Data Science internship (June–August 2027) working on machine learning, deep learning, and large-scale data analysis. Interns evaluate modeling tools, integrate internal and external data/APIs, design data science models, and present insights to stakeholders. In-person attendance at an assigned U.S. location is required; interns may be considered for full-time roles after graduation.

Lead the Software Asset Management engineering team: set technical direction, manage product development and releases, drive testing and automation, integrate AI/ML features, mentor engineers, and coordinate cross-functional and global teams to ensure scalable, high-quality enterprise solutions and 24x7 support.

Lead and deliver large-scale AI/ML programs and the next-generation Generative AI platform. Build and grow a world-class TPM discipline, manage cross-functional delivery, mitigate technical risk, and drive execution across product, engineering, design, and data science to achieve business impact in regulated environments.

The Senior Product Manager will lead data classification capabilities in a Data Security platform, overseeing product strategy and collaborating with various teams to drive accuracy and compliance.

Lead diverse technology projects and a team to create solutions for regulatory needs, leveraging distributed microservices and collaboration with product managers.

Lead an AI platform team to design, build, and deploy agentic, reusable AI services for healthcare payment integrity and clinical workflows. Provide technical and strategic leadership, drive deployment automation, CI/CD, production observability, ethical AI practices, and cross-functional partnership to ensure secure, scalable delivery and measurable business outcomes.

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.

Senior-level engineer delivering analytics and ML-Ops solutions for healthcare payers. Design and implement analytics platforms on Databricks, develop CI/CD and provisioning patterns, collaborate with data scientists, mentor juniors, and build client relationships to drive actionable insights and operational improvements.

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.

Lead research and development of emerging ML (embeddings, foundation models, transformers). Build and productionize machine learning models at scale, partner with product and engineering, analyze large-scale transactional and clickstream data, and run experiments to improve customer experiences across marketing, servicing, and fraud domains.

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.

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.

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

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