Artificial Intelligence Jobs in San Jose, CA

The role involves leading developer relations for AI platforms, guiding partners on product integration, and fostering collaboration for ecosystem growth.

The role involves designing, building, and deploying compute and networking solutions for AI and HPC, supporting customers with integration and performance debugging.

As a Senior Solutions Architect, you will assist customers in building solutions with NVIDIA's AI technology, focusing on Generative AI and Large Language Models while collaborating across teams for performance analysis.

Lead and architect AI agent applications by improving reliability, performance, and scalability. This role focuses on full-stack development, operational excellence, and collaboration across teams to build robust production systems.

Lead engineering team to develop AIPerf, an open-source benchmarking tool for LLM inference performance, while overseeing technical direction and mentoring engineers.

As a Senior AI Systems Performance Engineer, optimize and scale foundation models, enhance performance across various system layers, and deliver high-performance AI applications.

Full-cycle technical recruiter responsible for sourcing, screening, and closing AI/ML and computational biology talent. Build candidate pipelines, run first-round technical screens, design interview frameworks, manage ATS data, represent the company at conferences, and partner with founders on hiring strategy and offers including salary and equity negotiations.

Apply deep battery-systems expertise to define SOC/SOH/thermal states and BMS logic, incorporate safety constraints, design agentic AI decision frameworks, analyze large-scale vehicle and telematics data with Python, and collaborate across BMS, data science, and AI teams to develop adaptive battery management strategies.

Lead the architectural design for AI hybrid inference systems, mentor team, and guide development of high-availability orchestration engines while driving innovation.

Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.

Lead AI technical strategy, architect AI systems, set safety standards, mentor engineers, and evaluate AI models at Midi Health, a healthcare-focused company.

You will design and build LLM-powered features, integrate AI capabilities into workflows, and contribute to internal practices at a healthcare-focused company.

The role involves leading AI networking system transformations, collaborating with teams on product features, and managing customer engagements for innovative networking solutions.

As a Senior AI Frameworks Engineer, you'll develop high-performance APIs and infrastructure for GPU programming, ensuring a seamless developer experience in AI and deep learning contexts.

The role involves developing AI applications for VLSI design using machine learning and related technologies. Duties include infrastructure design, AI solution implementation, collaboration with teams, and maintaining design databases.

Develop high performance AI systems for GPU ASIC design flows. Collaborate with teams to integrate AI workflows into existing processes.

The NCX Engineer will develop custom AI solutions, provide technical support, manage AI workloads, and optimize performance on NVIDIA platforms.

The role involves developing AI models for fault-tolerant quantum systems, conducting research in quantum computing, and collaborating with teams to integrate AI solutions into quantum hardware.

The role involves developing AI systems software, implementing and optimizing kernels for AI workloads, and collaborating on deep learning frameworks and libraries.

Lead and mentor a team of 4-8 engineers to build and evolve AI developer tools for local and cloud GPU workflows. Define roadmaps with product partners, manage cross-team dependencies, drive technical execution, improve engineering efficiency via tools and automation, and ensure security and compliance.

Design and build multi-agent AI systems and RAG pipelines, orchestrate LLMs and embeddings, develop scalable full-stack (Node.js/Next.js) APIs, optimize infra (SQL, AWS/GCP, Docker/K8s), lead technical design-to-deployment, ensure code quality, and implement video content classification and tagging for influencer marketing.

Build and embed LLM-agent workflows into silicon engineering flows (RTL, verification, DFT, physical design, validation). Integrate agents with simulators, regressions, lab equipment, and CI; design rigorous evals, drive adoption, and accelerate chip development through measurable automation.

Lead enterprise sales and go-to-market for NVIDIA AI and accelerated computing with Lenovo: develop technical understanding, package joint solutions, co-market/co-sell across channels, build ecosystem partnerships, and drive integration, commercialization, and thought leadership.

Lead performance engineering for AV and robotics workloads: engage customers, develop parallel algorithms and GPU-optimized libraries, profile and tune GPU kernels, optimize distributed transformer communication using NCCL/NVSHMEM and interconnect strategies, and collaborate with architecture and system teams to influence next-generation hardware and software.

Design and scale production infrastructure for LLM-powered agents and copilots. Build reliable, high-performance services, APIs, CI/CD, and integrations; collaborate with research and hardware teams; mentor peers and drive continuous innovation in agentic AI applications.