Machine Learning Jobs in San Jose, CA

Design, develop, and deploy reinforcement learning, behavior cloning, and imitation learning models for autonomous truck behavior planning. Own reinforcement learning pipelines from environment construction through training and modeling, contribute to distributed training infrastructure, analyze model performance and failure modes, and collaborate with simulation and planning teams to deploy models across driving scenarios.

Design and optimize production machine-learning runtime pipelines for autonomous vehicle motion planning. Build high-performance C++ inference, feature extraction, trajectory generation, and orchestration components for embedded platforms. Develop validation, safety guardrails, fallback mechanisms, testing, monitoring, debugging, and observability tools. Investigate complex runtime failures and optimize latency, throughput, memory, and multithreaded performance while collaborating with machine-learning and systems engineering teams.

Design and develop complex software solutions for semiconductor equipment, lead projects, define specifications, troubleshoot software problems, and communicate with customers.

The Technical Product Manager will lead product direction, interface with engineering teams, and ensure the successful deployment of AI-powered safety systems. Responsibilities include defining product vision, translating customer needs, and maintaining high product quality.

Own, design, build, and operate core components of a high-throughput, low-latency real-time ad decisioning system. Take end-to-end responsibility for subsystems (architecture, implementation, testing, deployment, on-call), diagnose concurrency/timing issues, collaborate with applied scientists on ML-driven decisioning, mentor engineers, and drive system evolution and operational excellence.

Design and productionize machine learning solutions that predict and optimize GPU-accelerated Apache Spark workloads. Develop adaptive ML systems, AI agents, and optimization tools; collaborate with customers and partners on complex deployments; track advances in ML systems; and mentor engineers in data science and machine learning. The role requires expertise in large-scale data processing, modern ML/DL methods, LLMs, generative AI, reinforcement learning, online learning, feature engineering, and boosted-tree models.

As a Sr. Staff Machine Learning Engineer, you will drive the development of cloud security features, leveraging AI/ML to solve real-world challenges and optimize production systems.

Provide embedded legal counsel to product and engineering on privacy, IP, and consumer protection; lead Arena's global privacy program (GDPR, CCPA/CPRA, cross-border transfers); advise on AI governance and responsible deployment; support commercial contracts and data flow frameworks; build privacy processes, playbooks, internal agents, and legal-tech integrations to scale operations.

Architect role to design full-stack, large-scale solutions informed by leading tech companies. Requires deep ML/AI and large-data analysis knowledge, proficiency across languages/frameworks (Go, Scala, Python, R, MATLAB, Node.js, React), NoSQL expertise, and familiarity with mobile testing, deployment pipelines, and SRE practices. US work authorization required.

The Director of AI will lead AI and data engineering teams, define and execute AI strategy, and ensure effective partnership across functions, focusing on scalable AI solutions and responsible AI practices.

Lead development of large-scale reinforcement learning frameworks and simulation pipelines for autonomous vehicle foundation models. Design closed-loop simulation, optimize reward functions and simulation quality, build scalable data-processing workflows, and improve training reliability on GPU clusters. Develop monitoring and debugging tools while collaborating with platform, product, and research teams to integrate advanced model architectures and productize machine learning solutions.

Assist in developing software for autonomous driving vehicles, participating in project work involving machine learning, coding, and testing.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

The intern will design and implement AI-driven automation workflows to enhance the silicon testing process, collaborate with engineers, and document automation recipes.

The engineer will leverage AI to enhance pre-silicon verification processes, collaborate with teams, and improve methodologies using advanced tools.

Develop and validate compact transistor models (FinFET, GAA) and simulation methodologies for PDKs. Collaborate cross-functionally to ensure modeling readiness, perform statistical, RF and EM simulations, automate analysis with Python, and integrate innovative techniques like OMI and ML to meet delivery milestones.

Lead supply planning strategy for Boards and Systems products, develop scalable planning frameworks across components, ensure data integrity (BOM, yields, cycle times), accelerate time-to-market using advanced/AI planning, and manage global supply planning teams.

Lead the architecture and deployment of LLM-powered conversational chatbot systems, optimizing performance and ensuring scalability in a crypto environment.

Lead workload-driven AI/ML systems architecture across hardware and software. Own workload characterization, analytical performance modeling, KPI definition, and hardware performance analysis to guide SoC, memory, and HW/SW co-design decisions. Evaluate compute, memory, latency, and software bottlenecks; collaborate with CPU, compiler, runtime, and ML framework teams; present recommendations to leadership; and mentor junior engineers. The role requires expertise in processor and memory architecture, edge AI acceleration, performance modeling, and cross-functional technical leadership.

Bay Area-based hunter Enterprise Account Executive responsible for prospecting, developing, and closing new enterprise business for Anyscale. Manage complex sales cycles, achieve quotas, lead CxO engagements, qualify opportunities, collaborate with marketing, and drive ongoing account growth while advising customers on ML, compute, and cloud solutions.

Develop, evaluate, and deploy reinforcement learning methods for autonomous vehicle planning. Design real-time model architectures, build offline data-driven ML infrastructure, analyze fleet and field-testing data, optimize and deploy planning models, and collaborate with perception, software, and AI teams to deliver production autonomous driving systems.

Develop, optimize, and deploy computer vision and machine learning algorithms for autonomous robotics systems. Train custom models, including object detection, segmentation, and 3D vision architectures, for embedded platforms. Collaborate across teams to integrate algorithms into products, research emerging computer vision techniques, and maintain documentation and unit tests. The role requires strong PyTorch, C++, Python, multi-view geometry, deep learning, and robotics expertise.

The Applied Scientist will transform raw data into actionable insights by developing machine learning models for personalization, ranking, and optimization to enhance conversion and revenue. This role emphasizes building production systems, frameworks for experimentation, and communication with team members regarding technical challenges.

Seeking a Research Scientist to develop AI models for enhancing 3D reconstruction processes, requiring strong skills in computer vision and neural reconstructions.

Lead the unified Search and Voice product organization to define multi-year strategy and roadmap for the Roku Entertainment Assistant. Drive prioritization, cross-functional alignment, monetization, AI/ML innovation (LLMs, RAG, conversational AI), experimentation, quality, compliance, and measurable engagement and revenue outcomes while growing and mentoring a high-performing PM team.