Artificial Intelligence Jobs in Sunnyvale, CA

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.

Serve as a technical advisor for semiconductor customers and EDA developers to GPU-accelerate EDA and manufacturing workflows, apply ML/DL for inspection and yield, analyze architectures for acceleration, deliver trainings/demos, and collaborate with product and engineering teams to deploy scalable AI-enabled solutions.

Design and implement an MLIR-based AI compiler for GPU inference: develop graph representations and dialects, optimize performance and memory, define APIs, generate kernels, and collaborate with framework and hardware teams to enable new model patterns and GPU features.

Lead and evolve Coupang's core search experience using AI and machine learning, driving innovation, product direction, and measurable business impacts.

Support design, build, and deploy AI/ML models and AI-powered HR features (agents, chatbots, recommendations). Collaborate with HR, IT, and data teams, build HR data pipelines, document workflows, and handle sensitive HR data with confidentiality.

Lead design, build, and maintain scalable AI agents and backend systems for real-time, high-volume security operations. Integrate LLMs/GenAI, design data flows, APIs, databases, and enterprise authentication, collaborate cross-functionally, monitor and improve system reliability and compliance.

Support teams building AI workflows, automations, and agents; implement monitoring and anomaly detection; analyze and prepare operational data for model training; document workflows and update playbooks; test prototypes, evaluate performance, investigate issues, and track operational KPIs. Participate in learning, networking, and project showcases.

Lead technical programs with hyperscalers and OEM/ODMs to deliver AI datacenter infrastructure from design through production. Define schedules and milestones, translate customer requirements into cross-functional plans, resolve issues, manage qualification/validation, monitor factory production and yields, and communicate program health to customers and leadership. Champion post-deployment sustaining support and coordinate global teams to ensure timely delivery and customer acceptance.

Lead strategic technical programs with CSPs and ODM/OEM partners to deploy NVIDIA AI datacenter platforms. Integrate datacenter tools, operationalize AI factory processes, resolve blockers, manage timelines and cross-functional teams, ensure delivery of customer-specific features, and communicate program status and risks to senior leadership.

Lead architect and hands-on builder for AI solutions: evaluate feasibility and data readiness, translate business problems into technical and algorithmic requirements, design high-level architectures and prototypes, drive PoC to production handover, set MLOps/API standards, mentor team, and align North American implementations with European enterprise governance.

Lead architecture and implementation of agentic AI systems powering Zuma's platform. Rebuild onboarding and integration frameworks, implement analytics and observability for LLM performance, translate product needs into technical solutions, mentor engineers, establish engineering standards, and work directly with customers to enable scalable, production-grade AI experiences.

Lead end-to-end development and production deployment of agentic AI systems and full-stack products. Architect integrations with property management systems, improve reliability and observability, define engineering standards, and partner with product and operations to ship scalable AI agents across voice, text, and email.

Drive user growth and go-to-market execution for a new AI voice agent product through various acquisition channels and strategies while collaborating with cross-functional teams.

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.

As a Founding AI Engineer, you will develop an AI-powered knowledge platform, focusing on backend systems, machine learning data pipelines, and optimizing tech stack for performance while participating in the entire product lifecycle.

Lead design, build, and scale full-stack features for the Insights practice management platform using React, Python, and PostgreSQL. Improve reliability, observability, performance, and availability. Collaborate with infra and backend teams, mentor engineers, conduct code reviews, and drive architectural improvements while delivering high-impact projects aligned with product and design.

As a Senior Solutions Architect, you will assist customers in building solutions with NVIDIA's AI technology, focusing on Generative AI and Large Language Models while collaborating across teams for performance analysis.

The AI Research Scientist will develop and evaluate generative models for scientific data, collaborate with teams to apply AI in materials science, and mentor junior members while staying current in the field.

Embed with strategic customers to design, build, and deploy frontier AI/LLM systems into production. Responsibilities include discovery, architecture, integration, prototyping, deployment, observability, safety evaluations, and driving adoption and product feedback.

Develop physics-aware AI models and optimization workflows for semiconductor engineering. Design and train surrogate, operator-learning, and foundation models, build scalable data generation/training/deployment pipelines, collaborate with domain experts, and publish and drive adoption of Scientific AI solutions.

Own the inference performance product roadmap across the full stack, turning advanced LLM optimization techniques into widely adoptable platforms. Define strategies for agentic and multi-turn workloads, partner with open-source and internal teams to land optimizations, and own benchmarking, release readiness, regression tracking, and production feedback loops to improve latency, efficiency, and cost per token.

Lead technical strategy and execution for Merlin's AI Core platform across perception, sensor fusion, planning, and control. Build and manage a multidisciplinary engineering organization, own architecture from data pipelines to real-time onboard inference, enforce aviation-grade safety and quality, partner with certification and systems teams, recruit senior talent, and translate research into product opportunities.

Lead product for AI-native finance and ERP workflows: identify high-value opportunities, define workflow logic, automation vs. human handoffs, test with customers, and drive from problem discovery to business impact while collaborating with engineering, design, data, and marketing.