Artificial Intelligence Jobs in Santa Clara, CA

The VP will lead the North American HPC GTM strategy, manage a large sales team, oversee P&L, and nurture client relationships while achieving revenue goals.

Drive the development of agentic AI systems and lead cross-functional teams, influencing architecture, strategy, and technical direction within CUDA ecosystem projects.

Design and implement compiler optimization algorithms for deep learning inference, collaborate with framework and GPU architecture teams, define public APIs, and deliver high-performance AOT and JIT compilation with reduced memory and fast build times.

The role involves creating technical content and demos for AI applications in Supply Chain, collaborating with engineers, and training developers.

The Solutions Architect will assist customers in adopting NVIDIA's GPU hardware and software, deploying AI/ML solutions, and engaging with technical teams and customers.

Lead software initiatives and deploy AI models by coordinating cross-functional teams, managing programs effectively, and providing insights to senior management.

The Developer Relations Manager will support AI-native startups by providing technical guidance on NVIDIA technologies, fostering partnerships, and collaborating to solve engineering challenges.

Conduct original research in generative AI, implement and train large-scale models, collaborate with teams, and transfer technology to products.

Design and execute benchmarking methodologies for large-scale HPC/AI clusters, build and maintain telemetry/observability stacks (Prometheus, Grafana, DCGM), analyze performance across host, network and facility metrics, collaborate with hardware/software teams and customers to identify bottlenecks and optimize workloads, and contribute new benchmarking approaches for emerging workloads.

Manage developer and partner ecosystems for Edge AI and Functional Safety, guiding technical integration and adoption of NVIDIA technologies.

Seeking Machine Learning Systems Engineers to build end-to-end 3D native ML systems, focusing on training and inference challenges.

The AI Infrastructure Engineer designs, develops, and optimizes core capabilities for the AI inference platform, focusing on reliability, scalability, and operability of infrastructure and services.

You will design and build high-performance graphics systems for 3D generative AI, collaborating closely with artists and researchers to innovate production pipelines.

As a Generative AI Researcher Intern, you will develop large-scale 3D generative models, bridge research and product development, and collaborate with teams to advance 3D AI applications.

This internship opportunity is for students in computer engineering or AI to work on distributed systems at Bedrock Security.

As a Staff AI Solutions Architect, you will design, implement, and deploy AI solutions for cybersecurity, ensuring performance and security in production environments while mentoring engineers and collaborating across teams.

Lead and scale forward-deployed engineering pods to convert complex customer workflows into production AI agent deployments. Build operating cadence, quality bars, deployment playbooks, partner with product, and hire/coach leaders while staying technically hands-on to ensure reliable, observable, and safe agent systems.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

The Senior Staff AI Engineer will lead the design and optimization of reinforcement learning systems for enterprise applications, focusing on scalable architectures and production deployment. Responsibilities include mentoring, collaboration, and ensuring compliance with AI ethics and safety standards.

The Software Engineer will develop backend systems for an AI Energy Agent, including data integration, microservices, and scalable architecture, focusing on performance and reliability.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

Partner with executive sponsors and end users to identify high-impact AI use cases on Glean, run discovery workshops, scope pilots, build AI agents, drive adoption and expansion, and translate business needs into measurable outcomes.

Drive innovation for GPU clusters through platform management, identify gaps, develop projects, and engage with partners. Manage product roadmaps and self-service operations.

The role involves designing AI models and training methods leveraging wafer-scale hardware and collaborating with various teams and partners in AI and computational science.

The R&D Engineer will design and implement performance workloads on Cerebras' wafer-scale hardware, collaborating across teams to advance AI and scientific computing. Responsibilities include optimizing performance models, contributing to the technology roadmap, and publishing research findings.