Artificial Intelligence Jobs in San Jose, CA

Own strategic account growth and quota-carrying sales for AI infrastructure and datacenter storage customers. Develop multi-year account plans, manage pipeline and forecasts, lead complex negotiations, and build executive relationships. Position WD storage technologies within software-defined, hybrid cloud, HCI, data protection, and scale-out architectures. Drive design-ins, customer qualification, platform standardization, new technology adoption, proof of concepts, and long-term supply commitments through cross-functional collaboration.

Lead AI initiatives, establish strategy, and develop generative AI applications. Collaborate with teams to build and optimize financial products.

As a Principal AI Engineer, you'll design scalable AI systems, mentor teams, develop large-scale LLMs, and optimize AI-driven cybersecurity solutions.

The Forward Deployed Engineer interfaces directly with customers to assess and resolve security issues, delivering tailored AI and data-driven solutions, while documenting processes for broader application across customers.

Design, develop, and implement AI/ML models, manage AI solutions on cloud platforms, and collaborate with teams to optimize models.

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.

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.

As an AI Product Engineer, you will develop and deploy AI-driven software solutions, collaborate with customers, and optimize applications for real-world impacts.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

As a Backend Engineer at Brain Co., you will design, build, and operate backend services and data pipelines for AI products, focusing on robustness and scalability. You'll collaborate across teams and own the full service lifecycle while ensuring high availability and performance. You should have 3+ years of experience in production backend systems and a strong foundation in APIs and distributed systems.

The Principal Digital Design Engineer will architect and implement complex digital designs for connectivity solutions, oversee micro-architecture and RTL implementation, and mentor junior engineers.

Embed with customers to learn their workflows, redesign and build production GenAI/LLM systems on AWS, ship and operate code, evaluate non-deterministic models, and own business outcomes.

Lead global commercial strategy and execution for AI infrastructure sales across data center, edge, and industrial markets. Own revenue targets, build strategic partnerships with hyperscalers/OEMs, lead complex deals, scale a global sales organization, and align cross-functional teams on product roadmaps, supply chain, and market expansion.

The Senior Applications Engineer will design ATE test interface solutions, oversee hardware concepts, conduct PCB layout, and support customer testing requirements.

Design, build, and deploy LLM-powered tools, RAG-based knowledge systems, and agentic workflows to automate SOC integration tasks. Own reliability, evaluation, and observability for AI systems and collaborate with SOCD teams to scope, validate, and measure productivity gains from deployed automation.

Lead end-to-end technical programs to integrate AI (LLMs, agents, chatbots) into chip design workflows. Plan, coordinate, and drive cross-functional execution across ASIC, platform, and third-party partners, measure program metrics, manage risks, and translate user requirements into scalable production-ready AI capabilities for silicon development.

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.

The Sales Strategy and Operations Manager leads complex sales opportunities, develops ROI models, engages executives, and coordinates cross-functional input for compelling proposals.

Lead the development of large-scale video foundation models for humanoid autonomy, focusing on training strategies and model evaluation for real-world applications.

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

Develop learning systems using reinforcement learning for autonomous robots, focusing on policy optimization and real-world application.

The Helix AI Engineer, Modeling will design core model architectures for AI systems, focusing on multimodal inputs and improving model capabilities for humanoid robotics.

The Helix AI Engineer will design, train, and deploy large-scale generative models, focusing on diffusion modeling for robots, while enhancing robot autonomy through perception and world modeling.

As a Helix AI Engineer focused on pretraining, you will design and train foundation models using multimodal data, improve generalization strategies, and optimize distributed training pipelines.