Artificial Intelligence Jobs in Santa Clara, CA

Lead development and validation of LLM inference platforms for NVIDIA edge GPUs. Track open-source framework innovations, analyze model-to-hardware mapping, optimize GPU kernels and multi-node inference, produce performance reports, maintain developer inference recipes, own model bring-up workflows, and support partners on hardware-specific inference issues.

Analyze, profile, and optimize AI training workloads on NVIDIA GPUs across the hardware/software stack. Implement production-quality software, build MLPerf training submissions, model workloads in simulators, and develop automation tools to identify and resolve performance bottlenecks.

Design and implement AI-driven optimizations for software development workflows, leveraging LLMs and Agentic AI to enhance productivity and reliability.

Research, prototype, and implement methods to improve efficiency and deployability of LLMs, VLMs, multimodal models and agents. Focus on compression, quantization, inference and reasoning optimizations, novel architectures (MoE, SSMs, Looped Transformers), gradient-free methods, and inference-time optimizations. Build evaluation pipelines, run benchmarks, and contribute to publications, open-source, and IP.

The Staff Technical Product Marketing and Partner Marketing Manager shapes product strategies and develops marketing content, drives ecosystem growth, and builds sales relationships while collaborating closely with partners to enhance brand presence and pipeline growth.

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 Staff Software Engineer will lead the development of cloud-native AI platforms, optimizing AI workload deployment in Kubernetes environments and collaborating with cross-functional 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 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.

Build and operate regulator-grade, production AI-enabled full‑stack applications: real-time audit dashboards, CAAT/continuous-monitoring surfaces, and agentic human-in-the-loop apps. Own end-to-end stack from data modeling and APIs to React/Next.js UIs, ensure responsible-AI practices, data protection, audit trails, and drive adoption with non-technical auditors.

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%).

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.

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.

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.

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.

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%).

Design, build, and operate large-scale ML training and evaluation infrastructure for RL/AI research. Enable distributed, cost-aware GPU training, benchmarking, data curation, and continuous evaluation; collaborate with research and platform teams to productionize models.

Build and productionize scalable backend services, APIs, and AI workflows to connect requirements, modeling, validation, and test data for autonomous vehicle programs. Implement traceability, versioning, dashboards, and KPIs, refactor prototypes into certifiable systems, and collaborate with systems engineering, safety, and autonomy teams to support compliance and validation at scale.

Build and ship shared AI infrastructure, agent frameworks, and tooling; partner with product teams to productionize LLM and agentic features; own GenAI best practices for architecture, safety, evaluation, and deployment; develop agentic systems and AI SRE tooling; engage with customers to shape roadmap and demos.

Lead and manage a team delivering advanced AI/HPC and data center infrastructure solutions. Oversee planning, budgeting, solution design, pre-sales technical support, vendor enablement, reference architectures, KPI reporting, documentation, and cross-functional collaboration to ensure successful deployment of GPU‑accelerated compute, networking, storage, and facility solutions.

Short-term intensive research internship assisting in dataset collection and preprocessing, model architecture design and tuning, implementation of testing frameworks, analysis of model accuracy and bias, algorithm refinement, and documentation to support foundation-model research.

Short-term, intensive internship supporting foundation model work: prepare datasets, assist with model architecture and testing, analyze outputs for accuracy and bias, refine algorithms, and document findings for research collaboration.

As a Senior AI Developer Technology Engineer at NVIDIA, you'll design and optimize AI and HPC workloads, solve performance issues, and influence future hardware and software design.

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.