Artificial Intelligence Jobs in Santa Clara, CA

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.

Develop and maintain XR products and spatial UIs to interface with humanoid robots and data-capture hardware. Implement features, fix bugs, harden XR data sync, integrate custom hardware with XR headsets, and support hardware experiments, low-latency video streaming, and motion-capture workflows.

Architect, prototype, and deploy production-grade agentic and multi-agent AI systems for Media & Entertainment. Build high-performance RAG pipelines over multi-modal assets, optimize GPU inference and TCO on NVIDIA platforms, advise customers pre/post-sale, and create reusable reference architectures, blueprints, and technical collateral to scale solutions.

Own full sales and partnership cycle to bring voice AI to mobile service robots: engage senior robotics decision-makers, qualify and prioritize opportunities, close deals, and shape the commercial playbook while operating autonomously within a small technical team.

Lead technical engagements with robotics customers to design and integrate voice AI into mobile robots, own POCs and technical evaluations, clear deployment roadblocks, collaborate with sales/product/services, and feed customer learnings into the product. Travel across Europe for onsite evaluations (20–30%).

Lead AI-driven transformation of controllership and accounting processes: identify optimization opportunities, design AI-enabled workflows, develop pilots, partner with IT and finance SMEs, implement solutions, define metrics, ensure controls and change management, and build AI literacy across Controllership.

Lead technical customer engagements to design, build, and deploy GPU-accelerated AI/ML, DL, and data analytics solutions on cloud platforms. Create PoCs, run demos, collaborate with sales and engineering, deliver workshops and technical presentations, and troubleshoot customer deployments at scale.

Own the end-to-end product lifecycle for agentic AI features within an enterprise automation platform. Define roadmaps, engage customers for discovery and validation, partner with engineering/UX/applied AI to ship products, create PRDs and success metrics, track agentic AI research/trends, and support go-to-market execution.

Own reliability, observability, and delivery for a cloud-native, multi-tenant Kubernetes platform. Build CI/CD, GitOps, IaC, and AI-first automation for incident response and LLM infrastructure. Instrument SLOs and tracing, harden secrets and supply-chain security, troubleshoot production issues, and mentor engineers in AI-driven operations.

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.

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.

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.

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.

Build, deploy, and automate cloud-native infrastructure and applications using containers, Kubernetes, Terraform, and CI/CD. Integrate logs/metrics into AIOps platforms, enable SRE monitoring for SASE products, develop serverless functions, and create automated AI-driven detection and troubleshooting strategies.

Lead product marketing for Procore AI & Data products: own positioning, messaging, launches, competitive positioning, sales enablement, and cross-functional GTM programs. Collaborate with Product, Demand Gen, Sales, and global Marketing to create customer-facing content and drive adoption.

Own strategy and execution for a portfolio of AI-native and hyperscale customers. Serve as primary relationship owner, drive revenue, market share and product adoption, coordinate with solution architects, product marketing, OEMs and partners, forecast and train customers, and evangelize NVIDIA platforms to accelerate enterprise growth.

The role involves researching and developing GPU-accelerated AI workloads, optimizing algorithms, and collaborating with technical experts to improve hardware performance.

Lead a team to optimize algorithms for Deep Learning and Machine Learning, define technical initiatives, and collaborate with various teams for hardware and software innovation.

Drive design wins and market expansion for FPGA-based Physical AI solutions across robotics, autonomous systems, industrial automation, and edge AI. Own market strategy, customer engagement, ecosystem partnerships, sales enablement, and cross-functional feedback to product and engineering. Support technical sales, produce reference architectures and ROI analyses, and convert opportunities into long-lifecycle platform wins.

Lead the development of AI applications, ensuring high reliability and performance while collaborating with teams to identify use cases and implement scalable solutions. Drive AI methodologies, governance, and continuous improvement in the organization.

The AI Intern will support the deployment of multimodal models onto vehicle-grade platforms, assist with model optimization, and help ensure reliable performance in autonomous driving applications.

Design and implement hardened Kubernetes integrations and automation pipelines for hybrid-cloud AI workloads. Provide operational support, troubleshoot production systems, collaborate with customers and engineering teams, and contribute to open-source projects to scale AI infrastructure.

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.

Lead frontend development for an AI-driven finance automation platform: build a scalable React+TypeScript design system and interactive UIs (workflow builders, action libraries, observability dashboards, data type management), integrate REST APIs, collaborate with product/design/backend, and own features end-to-end while providing backend support when needed.