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About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
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The Senior Technical Program Manager - LLM Safety joins the team to lead cross-functional planning and execution for evaluation identification, selection, and execution. This role focuses on agentic-safety evaluations, including multi-turn tool calling, unsafe tool use, and unintended actions. You will translate technical safety priorities into executable programs covering LLM security, frontier risks, hallucinations, and agentic safety for Nemotron models. Responsibilities include establishing governance for reviewing safety findings, tracking multi-modal and multi-lingual evaluations, and building dashboards for executive reporting. Required skills include a deep understanding of LLM architecture, frameworks like OpenAI, Anthropic, and Hugging Face, and experience with post-training, inference, and Red Teaming. You will solve complex problems regarding data poisoning, model manipulation, and ensuring release-readiness through documented safety evidence and risk-acceptance decisions.
What does a Technical Program Manager earn in California?
Median $200000 from 105 postings across 25 companies.
Lead cross-functional planning and execution for identifying, selecting, and executing safety evaluations.
Focus on agentic-safety evaluations including multi-turn tool calling, unsafe tool use, and unintended actions.
Translate evaluation findings into prioritized mitigation plans with accountable owners and measurable closure criteria.
Manage end-to-end safety planning for Nemotron models, including scope, dependencies, risks, and release-readiness.
Establish and track multi-turn, multi-modal, multi-lingual, and long-context model evaluations across various domains.
Establish governance for reviewing safety findings, assigning severity, and determining release impact.
Document required safety evidence, approvals, exceptions, and risk-acceptance decisions prior to model release.
Build and maintain dashboards for executive reporting on evaluation coverage, critical findings, and mitigation progress.
What we're looking for
Bachelor’s degree or equivalent experience in computer science, engineering, data science, or a related technical field.
10+ years of experience in technical program management, engineering, product development, technical operations, or a similar area.
Strong understanding of LLM architecture, frameworks (e.g., OpenAI, Anthropic, Hugging Face), and model evaluation.
Familiarity with LLM development, post-training, inference, tool calling, evaluation datasets, and model-release lifecycles.
Experience directing programs related to AI/ML development, model evaluation, agentic safety, security, content safety, hallucinations, and/or production releases.
Familiarity with AI safety risks such as hallucinations, timely injection attacks, unsafe tool use, data poisoning, model manipulation, and unintended agent behavior.
Experience supporting model-safety evaluations, Red Teaming, adversarial testing, security assessments, or responsible-AI programs.
Ability to interpret technical evaluation findings and communicate their product, schedule, and release implications to leadership.
Hardware Development
Cloud Infrastructure
Technical Program Management
datacenter operations
Networking
Supply Chain
Risk Management
Product Development
Optics Switch Systems
Data Analysis
Debugging