Artificial Intelligence Jobs in Sunnyvale, CA

Own go-to-market strategy and positioning for NVIDIA desktop AI products. Lead cross-functional teams through planning, launch, and post-launch optimization. Coordinate OEM and channel messaging, train regional sales, collaborate with product/sales/marketing, and drive analyst/influencer relations to grow pipeline and sell-through.

Audit and monitor data labeling outputs, provide actionable feedback, support onboarding and training of annotators, enforce and improve guidelines, escalate workflow issues, and document findings to maintain high-quality human-in-the-loop AI data processes.

Evaluate AI model outputs, perform audit-based reviews, apply and improve guidelines, identify trends and failure modes, document findings, and collaborate with leads and cross-functional teams to refine quality standards.

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 Senior Staff AI Engineer will design, develop, and optimize reinforcement learning systems for enterprise applications, ensuring effective integration and compliance with ethical standards.

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.

Design and develop large-scale multimodal transformer models that fuse camera, LiDAR, and radar. Research cross-modal attention and token-fusion strategies, build scalable distributed training pipelines, explore self-supervised/contrastive pretraining, and optimize models for real-time, low-latency inference.

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

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 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 AI/BI product experiences that make natural-language data queries and AI-generated insights intuitive, transparent, and actionable. Lead end-to-end design from exploration to validation and action, collaborate with product and engineering, define AI-native enterprise patterns, and influence long-term AI/BI strategy.

Build a scalable platform around foundation models and LLMs, architecting multi-step, stateful workflows and high-performance infrastructure to manage asynchronous, parallel queries and enable autonomous research.

Research and implement core algorithms for a self-improving reasoning engine. Develop data-efficient methods to probe LLMs, extract hidden knowledge, synthesize fragments into reliable answers, and design autonomous self-improvement loops. Publish and bring novel ideas to production.

The role involves leading product engineering and manufacturing execution across North America, ensuring quality and performance of NVIDIA products by troubleshooting, coordinating with manufacturers, and analyzing factory data.

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.

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 AI Product Designer will lead the design process for AI products, collaborating with diverse teams to create user-centered solutions and drive product strategies while ensuring ethical design practices.

Architect and build production-grade AI applications and shared platform services across desktop, mobile, web, and cloud. Lead full-stack engineering, CI/CD, observability, and operational excellence. Build foundations like agent orchestration, memory/context services, evaluation frameworks, telemetry, and workflow execution. Operationalize NVIDIA AI technologies, collaborate with cross-functional teams, mentor engineers, and drive architectural alignment to deliver scalable, reliable enterprise AI products.

Serve as a technical advisor for semiconductor customers and EDA developers to GPU-accelerate EDA and manufacturing workflows, apply ML/DL for inspection and yield, analyze architectures for acceleration, deliver trainings/demos, and collaborate with product and engineering teams to deploy scalable AI-enabled solutions.

Provide technical leadership to industrial engineering accounts, helping CAE/CFD/FEA ISVs and OEMs GPU-accelerate solvers, apply physics-informed ML and Omniverse digital-twin workflows, analyze architectures for performance, and deliver trainings, demos, and customer-facing solution builds to drive adoption on NVIDIA platforms.

Design and deploy generative AI and multi-agent conversational systems for healthcare. Curate and extract clinical variables from unstructured EHR and claims data using LLMs and NLP. Build automated evaluation pipelines for agent safety, accuracy, and compliance. Ensure data privacy and validation for production releases and communicate results to cross-functional audiences.

Build and deploy production-grade AI/ML inference systems for a cloud security platform. Optimize LLM serving (vLLM, SGLang, KV cache), implement model evaluation/reporting, and collaborate with ML scientists and engineers to execute the AI roadmap.

Design, develop, and deploy document AI and multimodal pipelines (OCR, LLM reasoning, extraction validation). Lead pre-sales technical engagements, build POCs/demos, support sales with technical value propositions, deploy solutions across cloud and enterprise VPCs, and collaborate with product and partners to drive customer adoption and roadmap feedback.

This role involves driving new client acquisition and revenue growth through full-cycle sales execution and relationship building with stakeholders, while maintaining pipeline tracking in CRM.