Top Generative AI Jobs in San Francisco Bay Area, CA

In this role, you will design and deploy advanced machine learning and Generative AI solutions, leading projects from conception to deployment while mentoring junior team members.

Own and improve the AI Social render pipeline and agent loops that generate on-brand Instagram carousels and reels. Build prompts, structured outputs, tool-calling, and media composition to ship high-quality generative image, video, voice, and music products in collaboration with product, design, and content strategy.

Develop infrastructure and tools to integrate Generative AI into enterprise applications. Build scalable end-to-end ML pipelines on heterogeneous hardware, collaborate with data scientists to train/fine-tune models, lead product development for the Generative AI suite, mentor junior engineers, and own production deployments.

Lead design and build of Generative AI infrastructure and tools, deploy large-scale ML/LLM models to production, enable scalable ML pipelines on heterogeneous hardware, collaborate with product and data science, lead cross-team architecture and technical discussions, manage projects, and mentor engineers.

Design, build, and deploy LLM-based applications and multi-step AI workflows (retrieval, orchestration, agents) using large-scale structured and unstructured data. Partner with engineering to productionize solutions, implement evaluation and safety measures, ensure compliance and data governance, and communicate results to technical and non-technical stakeholders.

Design, implement, and train large-scale diffusion models for generating 3D worlds. Drive end-to-end model development including data curation, experimentation, evaluation, deployment, and collaboration with research, engineering, and product teams. Mentor colleagues and integrate cutting-edge generative AI research into production-ready systems.

Lead product strategy and execution for C3 Generative AI. Define technical requirements, collaborate with engineering and data science, drive roadmaps, manage go-to-market, monitor product metrics, and iterate based on customer feedback to deliver scalable enterprise AI solutions.

Lead design and delivery of production LLM systems for drug discovery: build RAG pipelines, hybrid retrieval, text-to-SQL, agentic workflows, evaluation frameworks, and orchestration for scientific analyses.

Design, develop, and deploy production-grade generative AI and agentic systems (LLMs, RAG, AI agents). Build document intelligence, retrieval pipelines, vector search, and monitoring frameworks. Collaborate with risk, compliance, product, and engineering to deliver scalable, governed GenAI solutions in regulated environments.

Lead generative AI image production for realistic personas and models. Build and optimize scalable generative pipelines, automate batch workflows, evaluate new models/tools, define technical direction and best practices, and improve image quality, consistency, speed, and cost-efficiency.

As a Software Engineer focused on generative AI, you will design scalable AI services, optimize APIs, and collaborate with cross-functional teams to enhance enterprise-wide transformation.

Conduct research to develop generative and sampling models for molecular systems, integrating probabilistic inference, deep learning, and reinforcement learning. Design, train, prototype, and benchmark diffusion, autoregressive, flow-based, and latent-variable architectures. Map between simulation and reality, collaborate with chemists and physicists, and work with engineers to deploy scalable research on distributed compute. Contribute end-to-end from ideation to production in a hybrid San Francisco/New York environment.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

Review, evaluate, and annotate AI-generated text, images, audio, and video in Simplified Chinese. Perform quality checks, identify edge cases, participate in calibration, and provide feedback to improve datasets and annotation guidelines.

Review, evaluate, and annotate AI-generated text, images, audio, and video; perform quality checks for accuracy and guideline compliance; identify edge cases and inconsistencies; contribute to dataset creation and calibration; provide feedback to improve annotation workflows and guidelines.

Architect and optimize large-scale GPU AI infrastructure: profile distributed training/inference, diagnose networking and system bottlenecks, design high-performance clusters, lead POCs, automate benchmarking, and drive technical engagements with customers and internal teams.

Serve as business product owner for Generative AI across commercial functions, driving POCs, pilots, and scale with IT. Lead AI governance, regulatory alignment, cross-functional use cases, vendor evaluation, and AI literacy. Coordinate stakeholders, articulate business value, and ensure sustainable deployment of GenAI solutions across affiliates.

Lead research and development of generative AI and NLP models for large-scale email data. Innovate on fine-tuning (LoRA/adapters), quantization-aware training, and knowledge distillation to meet strict latency budgets. Build scalable training/evaluation pipelines, establish robust evaluation frameworks (LLM-as-a-judge, synthetic and human-in-loop), integrate AI-augmented developer tools, and set long-term technical direction while mentoring researchers and driving production-ready model deployments.

Develop, train, evaluate, and deploy spatial generative AI models for home renovation and design. Define inference framing, prepare image-based datasets with labeling partners, iterate with user feedback, and deploy performant models into production architecture.

The Senior Software Engineer will design and implement Generative AI solutions, collaborate with teams, enhance AI applications, and mentor others in best practices.

Design and execute ML research and end-to-end model development for generative and summary-generation systems. Lead rigorous experiments, translate findings for stakeholders, partner with engineers to deploy models, track state-of-the-art advances, and define roadmaps to improve promotional writing and discovery for members.

Integrate LLMs, RAG, and agentic-AI into secure decision-support software. Design prompts and inference workflows, connect AI to backend services, evaluate outputs, build tests, document designs, and collaborate with engineering, security, and DevSecOps teams to deliver reliable mission-capable AI features.

Senior technical leader responsible for architecting and operationalizing generative AI across the enterprise. Drive end-to-end GenAI architecture, select models and agent frameworks, productionize RAG and agent solutions, ensure observability, guardrails, and cost optimization, integrate with AWS and DevOps toolchains, advise CXO stakeholders, shape AI strategy, and define governance and upskilling programs.

Lead architecture and delivery of Generative AI solutions across Life & Annuities insurance, defining secure, scalable patterns (RAG, vectors, agents), integrating AI with policy administration, underwriting, and third-party systems, and enforcing governance, observability, and compliance while mentoring engineering teams and guiding cloud and data platform choices.

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.