Artificial Intelligence Jobs in Santa Clara, CA

Lead presales for data and AI initiatives: design and present Microsoft Fabric-based data platforms, run discovery and AI workshops, scope proposals, translate technical designs into business value, mentor delivery, and support go-to-market and thought leadership.

Founding iOS engineer to own end-to-end consumer iPhone app: architecture, hardware pairing, media capture, onboarding, core user surfaces, analytics, and App Store releases. Set iOS architecture and coding standards, drive high-quality TestFlight/App Store release cycles, and collaborate with Android, hardware, and backend teams while growing the iOS team.

Lead development of the application and cognitive layer for humanoid robots: implement behavior trees and intent-to-action orchestration, build voice applications and multi-modal fusion, integrate robotics capabilities and edge/cloud AI services, and ensure production readiness with CI/CD, telemetry, and monitoring.

Work on client-side AI for Windows/Linux PCs: collaborate across teams and partners to optimize AI inferencing pipelines, perform end-to-end performance analysis, and implement compute/memory optimizations (quantization, pruning, distillation) to fit large models on edge devices.

Lead rebuilding NVIDIA's silicon productization toolchain using applied AI: simulate power and binning, convert silicon behavior into context-engineered AI agents, integrate tools into an agent harness, drive eval-driven development and CI gates, and mentor engineers to deploy LLM-backed production services that protect product quality.

Design and deploy LLM-powered validation pipelines and AI integrations for silicon design toolchains. Collaborate across teams to identify AI opportunities, build productionized agentic workflows, evaluate emerging AI tech, and measure impact with data systems to improve validation, characterization, and automation of chip bring-up and verification.

Architect, build, and deploy LLM-powered AI systems and automation to accelerate post-silicon validation and toolchain workflows; integrate AI across engineering teams, evaluate emerging frameworks, measure impact, and operationalize solutions from prototype to production while supporting silicon bring-up and lab debug.

Lead architecture and delivery of an ML infrastructure efficiency platform across silicon co-design teams. Define platform contracts, onboarding, orchestration, auth, observability, storage/caching, and SLA enforcement. Own production operation, security, reliability, and performance while mentoring engineers and driving cross-team technical decisions.

Lead AI search, SEO, and SEM strategy for Altera: optimize content and technical SEO, manage paid search campaigns, measure AI citation metrics, and coordinate cross-functional reporting and execution to drive organic and paid search growth.

Lead the AI Center of Excellence operating model as the CAIO's strategic chief of staff. Own executive cadence, governance, resourcing, cross-functional dependency management, partner delivery discipline, portfolio health tracking, and executive materials to accelerate decisions and shipped business value.

Lead development and operation of a governed data plane (certified data products, semantics, lineage, registries) powering BI and agentic AI. Build lakehouse, vector, and graph retrieval foundations; deploy agentic workloads for metadata generation, entity resolution, quality scoring, and unstructured classification. Manage AI Data Engineers, set standards, and drive cross-functional collaboration to ensure data reliability, certification, and production-ready AI platforms.

Lead design and delivery of an agentic AI Fabric: runtimes, orchestration, model gateway, and MCP/A2A integration spine. Own agent identity/entitlement, audit and GxP/Part 11 compliance, shared eval harness, and manage AI Harness Engineers. Drive architecture, standards, and enterprise adoption of agentic workflows and safe sandbox-to-certified promotion processes.

Lead development of local AI agent frameworks and optimized runtimes on Windows for GeForce RTX PCs. Ensure secure, sandboxed execution and privacy-aware inference routing, collaborate with AI research and driver teams, mentor engineers, and produce production-ready code for autonomous, always-on desktop AI assistants.

Lead development of local AI agent frameworks and runtimes on Windows for GeForce RTX PCs. Optimize GPU-accelerated LLM inference, enforce policy-based privacy and sandboxing, collaborate with research, driver, and open-source communities, mentor engineers, and produce production-ready code and deployment guidelines.

Build and maintain an agentic platform that transforms high-stakes medical and legal casework into structured context. Work across the full stack: agent architectures, eval frameworks, data ingestion/indexing, and user-facing tooling. Ship workflows, design reliability-focused evals and guardrails, iterate with user feedback, and set patterns for AI-native development in a healthcare context.

Lead development of local AI agent frameworks and runtimes on Windows and GeForce RTX GPUs. Optimize agent inference, sandboxing, and privacy/security policies, collaborate with AI research and driver teams, mentor engineers, and deliver production-ready, local autonomous agent systems.

Build and operate scalable backend services and data platform integrations for customer profiles, consent, personalization, campaign operations, and marketing intelligence. Design APIs, service integrations, and reusable platform capabilities; modernize database and identity systems; ensure reliability with observability, automation, and incident prevention; partner with cross-functional teams to translate business needs into production-ready solutions using AI-assisted engineering responsibly.

Develop, optimize, and ship video processing, generative video, and 3D reconstruction algorithms (e.g., NeRF, 3D Gaussian Splatting) across desktop and mobile. Integrate and deploy deep learning models, run research and evaluations, build production-ready modules, and create test environments and tools for runtime verification of video and 3D pipelines.

Develop and enhance visuomotor manipulation policies for humanoid robots, focusing on real-world deployment and integration with other systems.

Architect and implement low-latency sensor-to-GPU data pipelines, develop system software, drivers, and APIs, work across FPGA, networking, and CUDA stacks, integrate diverse sensors into Holoscan, and debug and optimize real-time distributed systems under strict latency and throughput constraints while collaborating with hardware, firmware, and AI teams.

Lead architecture and build AI-native developer tooling and autonomous agent systems to accelerate engineering workflows. Drive platform standards for reliability, safety, observability, and cost-efficiency while partnering across teams and mentoring senior engineers.

Lead global product strategy and lifecycle for large-scale network orchestration, telemetry, and analytics products. Define technical use cases and architecture requirements, guide cross-functional teams, engage customers and partners, and deliver scalable datacenter networking solutions aligned with NVIDIAs AI infrastructure roadmap.

Lead GPU and NVLink-based cluster design and validation for large-scale AI and HPC deployments. Advise cloud partners on architectures, perform performance modeling, debug deployment issues, support NPI rollouts, and relay field feedback to engineering.

Lead 0→1 product development for Emerald Cloud Services: define vision, conduct customer discovery, set product requirements for AI compute provisioning and management, partner with engineering and GTM teams, and launch and scale cloud services for enterprise and AI customers.

Design and evaluate machine learning algorithms focused on autonomy and perception, prototype solutions, conduct experiments, and transition prototypes into production.