Artificial Intelligence Jobs in Santa Clara, CA

Lead enterprise AI platform strategy and implementation across the bank. Build and manage multidisciplinary teams, establish AI governance, mitigate bias/privacy risks, integrate AI into core systems, collaborate with risk/legal/compliance, drive platform delivery, upskill staff, and track AI performance metrics for business impact.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

Own the full QA lifecycle for AI-powered legal solutions: design and run unit, integration, system, performance, and scalability tests; integrate automated suites into Azure DevOps CI/CD; generate and evaluate AI-assisted test cases; maintain defect tracking and quality metrics; collaborate with security and engineering teams to ensure production-ready releases.

Lead product strategy and roadmap for NVIDIA's PyTorch compilers and shared representation layer. Define priorities for torch.compile, agent-native compiler workflows, and inter-kernel optimizations. Partner with engineering and external customers, set success metrics and performance gates, and drive upstream OSS contributions and go-to-market plans to deliver measurable performance and adoption.

Design, implement, and optimize embodied AI model architectures and deploy them at scale. Build training/evaluation infrastructure and large-scale data pipelines combining simulation, teleoperation, generative and real-world data. Work hands-on with robot hardware (manipulators, mobile robots, RGB-D and tactile/FT sensors) to debug failures and close the sim-to-real loop. Collaborate with global research and hardware teams to integrate systems into consumer products.

Lead design and delivery of AI/ML systems for customer success and support: build production LLM/RAG assistants, model lifecycle and MLOps, low-latency ML services, safety/governance controls, and full-stack integrations (frontend, backend, cloud). Drive observability, KPIs, experiments, and cross-functional partnerships while mentoring engineers and shipping scalable, secure AI features.

Lead system marketing for Renesas Power Product Group focused on datacenter and data infrastructure. Drive system architecture projects, market and competitor analysis, roadmap input, sales support, collateral and demo development, and global campaign content to increase adoption of Renesas power solutions.

Build AI systems that autonomously turn new model architectures into verified, production-ready kernels optimized for Etched hardware. Develop agentic tooling to generate, compile, profile, and iterate on implementations; design evals for correctness, stability, latency, and efficiency; turn profiler traces and hardware signals into learnable datasets; ship model-generated improvements and partner with architecture teams to influence hardware-software roadmap.

Embed with enterprise customers to deploy production agentic AI workflows: integrate data sources, identity, CRMs and APIs; handle security, SSO/SCIM, isolated VMs and compliance; drive adoption, instrument usage, and feed product improvements to scale deployments.

Embed with enterprise customers to design, build, and deploy production agentic AI workflows. Integrate platform with customer systems, handle security and compliance reviews, drive adoption and expansion, and feed product improvements based on field signal.

Join Hiring.Cafe as a Founding Machine Learning/AI Search Engineer to develop AI recommender systems and scalable infrastructure, contributing to a transformative job search engine.

The Head of AI Applications will define and execute the AI strategy within SiTime, leading the development and deployment of AI solutions across various business functions while driving adoption and managing a high-performing team.

Drive deployment of NVIDIA GPU and networking solutions at customer data centers: advise on network/compute/storage design, perform bring-up visits, debug performance, build POCs/demos, and liaise with product, engineering, and sales teams.

The Senior Systems Software Engineer will optimize AI stack readiness for the DGX Station, focusing on application performance, DL framework analysis, system-level optimization, and collaborating with cross-functional teams to enhance multi-GPU capabilities and ensure product effectiveness.

Develop tools for AI workload profiling and debugging in GPU clusters, collaborating with various teams to enhance performance and efficiency.

The role involves collaborating on AI GPU deployment, optimizing performance, mentoring engineers, and improving user experience on NVIDIA RTX platforms.

The Developer Relations Manager will engage research labs to promote NVIDIA's AI platforms, assess institutional opportunities, provide technical guidance, and connect with researchers to drive product development and collaboration.

Design and deliver high-performance, area- and power-efficient ASIC/GPU micro-architecture and RTL. Develop agentic AI solutions to craft micro-architecture, implement RTL, and produce fully verified, synthesis/timing-clean designs. Collaborate with designers and tool owners, and build LLM-powered engineering assistants, multi-agent systems, and multi-modal dialogue tools to accelerate chip design workflows.

The Staff Software Engineer will lead the development of cloud-native AI platforms, optimizing AI workload deployment in Kubernetes environments and collaborating with cross-functional teams.

Design, build, and deliver an AI and machine learning platform, enhancing developer velocity while collaborating with cross-functional teams.

As a Staff AI Research Engineer, you will develop AI solutions, implement machine learning algorithms, benchmark techniques, and transition prototypes to production.

Lead end-to-end silicon diagnostic pipeline using AI/ML to analyze scan failures and process data, build models for failure classification and predictive yield, orchestrate AI-based EDA tools, and drive cross-functional root-cause analysis to improve yield and time-to-market.

Build and operate regulator-grade, production AI-enabled full‑stack applications: real-time audit dashboards, CAAT/continuous-monitoring surfaces, and agentic human-in-the-loop apps. Own end-to-end stack from data modeling and APIs to React/Next.js UIs, ensure responsible-AI practices, data protection, audit trails, and drive adoption with non-technical auditors.

Quota-carrying sales executive responsible for sourcing, developing, and closing technology consulting engagements focused on AI. Manage full sales cycle from prospecting to proposal and contract negotiation, build and maintain pipeline, collaborate on go-to-market strategies, engage executive-level buyers, and participate in marketing events. Hybrid role with travel (~20-25%).

Enable end-to-end agentic AI GPU deployments on NVIDIA RTX and DGX by profiling and optimizing performance, contributing to open-source LLM/GenAI projects, delivering trainings and sample code, collaborating with drivers/architecture teams, and mentoring junior engineers.