Artificial Intelligence Jobs in Sunnyvale, CA

Build and prototype state-of-the-art large language models and AI assistants, take services from ideation to production, fine-tune open-source models, use LLM platforms, analyze model statistics and projections, and collaborate cross-functionally in a fast-paced hybrid Palo Alto environment.

Build infrastructure for AI/ML environments, collaborate with teams for improvements, and interact with customers to enhance product features.

Lead the design and implementation of scalable AI systems focusing on large language models and speech technologies, while providing technical leadership and mentoring.

Lead finance-focused AI and automation transformation: identify and prioritize high-value AI opportunities, run pilots and prototypes, define data and control requirements, and scale AI-enabled finance workflows while driving adoption, governance, and measurable value realization across Finance.

Lead developer relations for NVIDIA's local AI ecosystem: manage strategic partner portfolio, provide technical guidance, drive adoption of NVIDIA accelerated computing and runtimes, define joint plans and success metrics, enable partners with integrations and content, represent partner needs internally, and evangelize local AI at events.

Senior architecture leader defining and governing enterprise AI/ML platform architecture, standards, and guardrails. Drives cross-team alignment, vendor assessments, secure multi-cloud solutions, model governance, observability, and production readiness while advising executives and mentoring architects.

Lead US TMT business development with an AI focus: identify revenue opportunities from AI regulation, M&A, governance and data trends; develop client strategies, communications and targeted outreach; support pitches and major US TMT projects; coach and manage MBD colleagues; collaborate with partners and international teams to drive client relationships and revenue growth.

The role involves developing and productionizing security detection models, collaborating with security research, and shaping engineering culture as a founding team member.

Join the Fury Team as an AI Engineer to develop AI models for autonomous systems, designing architectures and integrating ML for real-time applications.

The AI Researcher will lead research in embodied intelligence for defense systems, focusing on reinforcement learning, vision-language modeling, and building scalable AI models for autonomous applications in real-world environments.

Lead research and architectural direction for AI systems communication at scale, conducting original research, optimizing hardware-software performance, and mentoring engineers.

The AI Compiler Engineer will innovate in AI performance, optimize compiler processes, and collaborate on hardware/software co-design, advancing AI technologies for datacenter applications.

Build end-to-end Ambient AI products for healthcare, work across the software stack, and engage directly with customers to resolve issues.

Develop AI-powered healthcare solutions, implement fullstack systems, collaborate across teams, and ensure usability in clinical environments.

Develop logic design and RTL coding for AI SoC products, integrate IP blocks, perform quality checks, and mentor junior engineers.

Design, build, and improve ML systems and infrastructure, mentor junior engineers, and write maintainable code in a customer-focused environment.

The AI Engineer will design and develop generative AI applications and manage their full lifecycle, ensuring operational efficiency and system performance while employing LLM technology.

As a Senior Product Manager for AI, you will lead AI-based product strategies, engage with customers for insights, prototype solutions, and collaborate with teams to deliver intelligent agent-driven products.

The AI Accelerator Silicon Architect will define compute architecture, analyze performance, and collaborate with teams on silicon architecture for AI workloads.

Lead a research team focused on enhancing large-scale machine learning models' efficiency and performance, developing novel algorithms and collaborating with engineering teams to implement breakthroughs.

Design, build, deploy, and operate large-scale GPU cloud infrastructure and tooling for AI training and inference. Perform performance analysis, capacity management, monitoring, automation, incident response, and lifecycle support for distributed multi-GPU/multi-node systems.

Lead research on human-AI perception and interaction: propose and prototype ideas, publish and patent results, build interactive demos, collaborate with engineers and external researchers, mentor interns, and transition research into products.

Responsible for forecasting, planning, and financial analysis, building analytical tools, and providing insights while supporting senior management across the GeForce FP&A team.

Design, build, and deploy production-grade agentic AI systems and scalable evaluation frameworks. Develop automated metrics to measure accuracy, safety, and reliability of non-deterministic agents. Automate and scale evaluation infrastructure to improve characterization and assessment of onboard autonomous driving software.

Lead architect and hands-on builder for AI solutions: evaluate feasibility and data readiness, translate business problems into technical and algorithmic requirements, design high-level architectures and prototypes, drive PoC to production handover, set MLOps/API standards, mentor team, and align North American implementations with European enterprise governance.