Artificial Intelligence Jobs in Sunnyvale, CA

Own end-to-end delivery of AI data projects, including scoping, planning, budgeting, scheduling, execution, risk management, and quality control. Serve as the primary liaison among clients, suppliers, and internal teams while managing annotated datasets and project outputs. Improve workflows, reduce costs, resolve issues, and develop scalable solution frameworks. The role requires strong communication, organizational, client-management, and cross-functional collaboration skills in a global environment.

Leads strategy, roadmaps, and lifecycle management for availability and observability platform products. Partners with engineering, architecture, operations, data, and AI teams to improve reliability, scalability, and operational visibility. Uses analytics, KPIs, and AI-enabled insights to guide product decisions, launches, adoption, and optimization. Manages complex requirements, influences stakeholders, mentors team members, and promotes continuous improvement and operational excellence.

Leads complex technical programs for an enterprise client, coordinating engineering, operations, and sales stakeholders. Responsibilities include defining outcomes, building delivery plans, managing risks and dependencies, establishing governance, driving change, and communicating performance. The role also requires applying AI agents to program orchestration, scaling program-management practices, and providing technical guidance on software development and platform architectures.

Lead customer robot deployments from workflow discovery and site assessment through scoping, financial modeling, technical alignment, execution, acceptance testing, training, and handoff. Partner with engineering, research, safety, solution engineering, customers, and external teams to define requirements, success metrics, dependencies, and milestones. Translate field feedback into deployment practices while managing scope changes, implementation tradeoffs, customer value, utilization, and support needs.

Leads NVIDIA’s autonomous vehicle software program portfolio, owning delivery roadmaps, governance, risk management, customer timelines, and cross-functional execution. Manages and develops a team of technical program managers while personally driving complex autonomy programs, integrations, design reviews, and issue resolution. Partners with engineering, testing, regulatory, product, and vehicle-program leaders to deliver autonomous driving features and communicate technical risks and decisions to executives.

Lead architecture and hands-on development of reusable customer-facing AI platform services, including conversational AI, agent orchestration, retrieval, grounding, memory, tool integration, and policy enforcement. Define APIs, data models, deployment designs, testing, evaluation, and operational requirements. Build production systems across GCP and Azure while driving reliability, security, observability, CI/CD, and technical standards. Provide staff-level influence through architecture reviews, mentoring, code reviews, and cross-functional leadership without direct reports.

Build infrastructure and tooling for AI evaluations, including distributed scoring engines, task-set validation, grader systems, human-review calibration, statistical leaderboards, online feedback capture, and offline-to-online evaluation loops. Partner with product, engineering, data, and ML teams to deliver reliable, observable evaluation workflows that support faster and more trustworthy AI product development.

Lead market success and adoption for an enterprise AI Assistant portfolio. Responsibilities include developing customer and market insights, preparing integrations for general availability, leading launches and early-access programs, gathering customer feedback, enabling sales and customer-facing teams, defining adoption metrics, shaping product requirements, and creating community and marketing content. The role requires extensive enterprise SaaS experience, integration expertise, strong technical understanding of deployment and security considerations, analytical skills, and exceptional communication.

Leads public relations for NVIDIA’s AI software business by developing compelling technical narratives, pitching reporters, securing media coverage, and building relationships with media and internal teams. The role translates complex AI, software, open-source, and model technologies into engaging stories that strengthen the brand and advance proactive communications strategies across industries.

Internship opportunities supporting General Intelligence and Robotics Centers. Work may involve foundation models, multimodal pretraining, reinforcement learning, autonomous driving, scalable AI infrastructure, inference systems, robotics, world models, embodied agents, manipulation, locomotion, and whole-body motion control.

Provides technical and strategic counsel to the Microsoft AI CEO on high-stakes research decisions. The role evaluates models, prototypes solutions, analyzes technical tradeoffs, and supports work spanning pre-training, post-training, multimodal systems, infrastructure, safety, and alignment. The advisor synthesizes technical findings into executive recommendations, drives initiatives from conception through execution, tracks emerging AI research, and facilitates communication between leadership and research teams.

Owns CoreWeave’s Physical AI communications strategy, including messaging, media relations, product and customer launches, executive thought leadership, technical content, and reporter relationships. The role translates AI infrastructure, robotics, autonomy, and scientific computing into credible narratives, advises senior leaders, coordinates cross-functional communications, develops customer and partner stories, and measures coverage and message performance.

Develop data-centric machine learning solutions for autonomous driving. Design dataset mixtures, curation and mining methods, model-training recipes, scaling studies, and offline evaluations using real and synthetic driving data. Apply self-supervised learning, imitation learning, reinforcement learning, and foundation-model fine-tuning. Train models across large multi-GPU and multi-node datasets, diagnose data-related failures, and collaborate on deploying models into onboard driving systems.

Manage strategic relationships with AI-native startups, drive revenue and quota attainment, qualify and close complex technology solutions, maintain forecasts, and collaborate with solution architects, channel partners, and cross-functional teams. The role requires positioning NVIDIA CUDA-X libraries, supporting startup integrations and go-to-market initiatives, and developing business and technical collaborations.

Owns the design, deployment, governance, and operation of enterprise AI platforms and employee-facing agents. Builds secure control layers including identity, access, device, tenant, MCP, secrets, logging, rate limiting, and cost controls. Establishes AI lifecycle processes, evaluates and rolls out new tools, operates infrastructure to SRE standards, and develops telemetry, dashboards, runbooks, and incident response. Partners with Security, Legal, Privacy, and IT teams to translate governance requirements into enforceable technical controls.

Architects and operates production-grade agentic AI systems for enterprise identity security. Responsibilities include designing multi-agent orchestration, tool use, planning, memory, retrieval-augmented generation, model integration, evaluation, safety guardrails, observability, and human-in-the-loop controls. The role provides technical leadership through architecture ownership, code reviews, mentoring, and establishing scalable production AI practices.

Develop and execute enterprise AI and data strategies for clients, including AI value cases, operating models, talent strategies, technology roadmaps, responsible AI plans, and commercialization opportunities. Build trusted C-suite relationships, lead transformation workstreams, shape new business opportunities, and guide large-scale AI-enabled reinvention initiatives. The role requires consulting experience, strong program management and communication skills, leadership capability, and up to 80% travel.

Design and lead cloud and in-car data mining strategies for autonomous vehicle perception and end-to-end models. Build AI-driven software to accelerate data mining, collection, delivery, and corner-case resolution. Develop operational processes using big data, statistics, and machine learning to ensure high-quality training data from production and collection vehicles. Collaborate with platform teams and balance cost, engineering quality, and delivery timelines.

Software Engineer Interns will own scoped projects from design through launch, building reliable, tested, production-quality software. They may contribute across backend services, product engineering, infrastructure, security, UI/full-stack, machine learning, NLP, or search. Interns will collaborate across teams, participate in code reviews, learn quickly, and measure project outcomes in a fast-paced environment.

Evaluate AI model outputs, conduct audit-based reviews, identify patterns and failure modes, apply and improve evaluation guidelines, and document actionable findings. The role requires native-level Marathi, strong English, structured writing, GenAI safety knowledge, critical thinking, and comfort making judgment calls in ambiguous situations. Associates collaborate with leads and stakeholders, participate in calibrations, and help refine quality standards. This is a full-time, one-year, 100% onsite contract role in specified U.S. cities.

Lead large cross-product initiatives within ServiceNow’s Security Design team, creating AI-native product experiences, cohesive security workflows, and end-to-end user journeys. Provide strategic design direction across multidisciplinary teams, develop high-fidelity product specifications and design frameworks, influence product strategy, and improve design processes. The role focuses on security lifecycle experiences including SOC automation, threat intelligence, exposure management, vulnerability response, and incident response.

Develop full-stack tools and automation for deploying and managing cloud infrastructure. Responsibilities include designing software solutions, collaborating with business partners, developing architecture and automation strategies, reporting on projects, and providing technical leadership. The role requires React and Go development, API integration, CI/CD, automated testing, version control, security-focused coding, troubleshooting, documentation, and applying AI technologies to improve workflows and decision-making.

Leads engineering teams building AI-native ITOM Discovery products. Owns technical strategy, architecture, delivery, reliability, hiring, coaching, and organizational development. Diagnoses architecture, UX, data, cost, and feedback-loop issues; establishes engineering standards and reusable patterns; and collaborates with Product, Design, Security, Operations, Sales, and Customer Success to align roadmaps, releases, compliance, and customer value.

Designs and develops secure, performant Copilot products and platform services across Windows, Mac, and mobile. Builds distributed AI and agent-driven systems capable of reasoning, planning, and executing tasks. Collaborates with infrastructure, platform, application engineering, and research teams to ship high-quality software. Champions AI-assisted development, coding-agent adoption, prompt design, tooling best practices, and human-in-the-loop systems.

Develops digital marketing strategy, user journeys, web experiences, campaigns, and acquisition funnels for cloud and AI platforms. Leads customer-focused optimization through UX research, A/B testing, reporting, and data analysis. Collaborates with product marketing, engineering, and operations teams to define requirements, improve digital experiences, support lead generation, and achieve web channel goals across global markets.