Artificial Intelligence Jobs in San Jose, CA

The role involves developing MLIR-based AI compilers for NVIDIA's inference engine, focusing on optimizations, APIs, and collaboration with hardware teams to enhance GPU performance for deep learning applications.

Lead the architecture and deployment of LLM-powered conversational chatbot systems, optimizing performance and ensuring scalability in a crypto environment.

As an AI Extern, you will optimize language models, collaborate with teams on machine learning solutions, analyze data, and enhance product functionality.

The Helix AI Engineer will design and develop multimodal autonomous agents, focusing on reasoning and reliability for humanoid robots using machine learning techniques and frameworks.

The AI Business Analyst will partner with HR teams to identify AI use cases, support the AiMEE chatbot, collaborate on HR analytics, and enhance employee experience through technology solutions.

The Lead Product Manager, AI will identify and build AI-powered products, drive growth and customer experience, and collaborate with cross-functional teams.

The role involves applying diffusion techniques and developing AI models to enhance 3D reconstruction pipelines for various industries.

The AI and Data Engineer will develop and enhance a Generative AI Platform, focusing on prompt design, testing, and optimization in collaboration with cross-functional teams.

As an AI Platform Backend Engineer, you'll design and deploy backend systems utilizing AI for real-world applications, optimize performance, and mentor junior engineers while working directly with clients to address complex challenges.

As an AI Platform Engineer, you will design and develop AI-driven backend solutions, optimize performance, and collaborate with customers and teams.

As an AI Intern, you will contribute to research on machine learning, develop market analyses, analyze AI usage in semiconductors, and propose project management improvements.

As a Senior Full Stack Engineer, you will lead software development from design to deployment, focusing on scalable services using Python and AWS technologies, while integrating AI tools and mentoring younger engineers.

As a Full-Stack Engineer at Labelbox, you will develop and maintain AI tools, focusing on data training systems, intermediate user interfaces, scalable architectures, and work in a collaborative, fast-paced environment.

Design and implement AI-native frameworks, optimize performance for deep learning models, and ensure high-quality software development using modern C++ and AI tools.

As a Senior AI Solutions Architect, you'll drive the use of NVIDIA AI solutions, support developers, and analyze application architectures to enhance performance.

Responsible for defining and validating SoC IP blocks, collaborating with teams to ensure quality silicon for AI applications, and mentoring junior engineers.

As an RTL Design Engineer, you'll develop RTL coding and simulation for SoC designs, optimizing logic for performance and power. You will collaborate with verification teams, implement microarchitecture features, and ensure design integrity in a fast-paced environment.

Lead a customer-focused engineering team in AI Networking, enhancing NVIDIA's networking capabilities and supporting customer initiatives in large-scale AI infrastructure.

The AI Intern will develop AI systems, design workflows for content analysis, and evaluate performance against technical expectations. This role involves working with LLMs and collaborating with engineers to create effective AI applications.

The Head of Applied AI will lead the AI team, manage architectural initiatives, foster a productive environment, and ensure the delivery of AI features that meet customer needs.

The Director of AI/ML will lead software engineering teams in developing scalable AI-driven cybersecurity solutions, setting the technical vision and managing project execution while fostering innovation and collaboration.

As a Senior AI Systems Performance Engineer, you will benchmark AI workloads, optimize Ethernet fabric performance, and troubleshoot system bottlenecks, focusing on delivering actionable insights across teams.

The internship involves multiscale modeling focusing on physics and AI modeling. Interns will run simulations and define workflows using Python and related libraries.

The Test Automation Engineer will design, develop, and maintain automated testing frameworks for network observability solutions, ensuring quality and reliability while collaborating across teams.

Lead the development of AI-driven machine learning solutions to optimize customer experience through personalization and recommendations, while guiding team technical direction.