Artificial Intelligence Jobs in San Jose, CA

Design and scale GenAI-powered product marketing capabilities: codify PMM methodologies, build agentic workflows and prompt systems, prototype with Python/Streamlit, and partner cross-functionally to productionize AI-enabled GTM, segmentation, and messaging workflows.

Lead finance-focused AI and automation transformation: identify and prioritize high-value AI opportunities, run pilots and prototypes, define data and control requirements, and scale AI-enabled finance workflows while driving adoption, governance, and measurable value realization across Finance.

Lead developer relations for NVIDIA's local AI ecosystem: manage strategic partner portfolio, provide technical guidance, drive adoption of NVIDIA accelerated computing and runtimes, define joint plans and success metrics, enable partners with integrations and content, represent partner needs internally, and evangelize local AI at events.

The role involves developing and productionizing security detection models, collaborating with security research, and shaping engineering culture as a founding team member.

Lead advanced analytics and AI initiatives in compliance, collaborating with data scientists and engineers, translating requirements, mentoring, and maintaining governance standards.

The role involves leading the product lifecycle for AI products, collaborating cross-functionally to define features, track success metrics, and enhance user experience.

Lead research and architectural direction for AI systems communication at scale, conducting original research, optimizing hardware-software performance, and mentoring engineers.

The AI Compiler Engineer will innovate in AI performance, optimize compiler processes, and collaborate on hardware/software co-design, advancing AI technologies for datacenter applications.

The Technical Account Manager will lead customer technical projects, provide architecture guidance, ensure product adoption, and serve as a trusted advisor to enhance customer success and satisfaction.

The AI Robotics Research Intern will focus on dexterous manipulation, utilizing large-scale data to improve robotic behaviors through human interaction insights. Responsibilities include developing scalable frameworks, processing data, and optimizing robotic policies for physical deployment.

The role involves researching and architecting next-gen AI systems, focusing on memory and communication bottlenecks, and collaborating on architecture-level design and performance modeling.

Lead and execute high-impact AI initiatives, serving as a technical authority on agentic systems and fullstack development, while mentoring and optimizing infrastructure strategy.

Lead and architect AI transformations at Broadcom, overseeing large-scale projects and serving as a technical authority on AI systems, ensuring innovative, scalable solutions.

Develop and optimize video processing applications and algorithms for desktop and mobile. Research and evaluate video processing and neural-rendering methods, implement modular, high-performance code, integrate and deploy deep learning models across Mac, Windows, iOS and Android, and build test environments and tools for runtime verification.

Architect, deploy, and manage large-scale AI training and inference infrastructure. Build and scale containerized, multi-cloud GPU compute, optimize LLM serving, maintain MLOps tooling (MLflow), and collaborate with researchers and engineers to productionize models and debug hardware-software performance bottlenecks.

Design, build, deploy, and operate large-scale GPU cloud infrastructure and tooling for AI training and inference. Perform performance analysis, capacity management, monitoring, automation, incident response, and lifecycle support for distributed multi-GPU/multi-node systems.

Lead research on human-AI perception and interaction: propose and prototype ideas, publish and patent results, build interactive demos, collaborate with engineers and external researchers, mentor interns, and transition research into products.

Design, implement, and evaluate machine learning and deep learning algorithms—especially ASR for live captioning—using C++ and Python. Build and optimize Conformer, RNN-T, Transformer encoder, and beam-search based systems, perform distributed GPU training, testing, debugging, and documentation. Work with large-scale computing frameworks and adapt ML technologies to VR/AR, robotics, and interactive products. Resolve complex problems, define methods for new assignments, and may coordinate other personnel.

Design and implement high-performance Vision AI pipelines and large-scale distributed services for processing video, image, and 3D data across edge and cloud. Build multi-modal perception, use simulation/synthetic data for testing, profile and optimize GPU-accelerated inference, collaborate with research and product teams, drive code quality and reviews, and mentor engineers to productionize vision models at scale.

Develop and deploy AI Ops solutions for Cisco's Circuit platform: evaluate and integrate LLMs, optimize token usage and routing, fine-tune models, build AI agents and agentic features, mentor peers, drive features from concept to production, and measure performance and cost-efficiency.

Lead development of AI-driven regression and agentic workflows to automate functional QA for the Circuit platform. Modernize legacy features, build validation frameworks, integrate AI-generated code into CI/CD, and drive cross-functional automation initiatives to improve reliability and reduce technical debt.

Build, deploy, and maintain end-to-end AI applications integrating ML models and LLMs. Develop scalable backends and REST APIs, create responsive frontends, manage MLOps and containerized deployments, and collaborate with data scientists and product teams to deliver AI-driven products.

The Director of Product will lead AI-powered seller tools, driving strategy, delivering features, and managing a high-performing team to enhance seller experiences.

Build and productionize AI applications integrating LLMs and vision models into an edge-to-cloud robotics platform. Fine-tune and quantize models, deploy to NVIDIA Orin/Jetson and cloud GPUs, integrate Vector DBs/RAG/agent frameworks, and create data pipelines to collect and version sensor data for retraining.

The AI Research Engineer will design, implement, and improve AI systems for therapy, enhance evaluation methods, and collaborate with various teams to innovate and ensure safety in AI therapy.