This role pays more than
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of similar roles. Most pay
$174,950–$222,907
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At the midpoint, this role pays about
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versus about
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Based on 240 similar postings.
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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
Nvidia currently has
896 open roles
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Listed pay typically runs
$184,000–$287,500
across 876 roles with salary data.
As a Senior Technical Program Manager - LLM Safety, you will join the team to lead cross-functional planning and execution for evaluation identification, selection, and execution. You will manage end-to-end safety planning for Nemotron models, focusing on agentic-safety evaluations including multi-turn tool calling, hallucination mitigation, and frontier risks. Your daily work involves translating technical safety priorities into executable programs, establishing governance for reviewing findings, and tracking metrics like release readiness and residual risk. You will build dashboards using AI for Code and AI for Work to report on evaluation coverage. The role requires expertise in LLM architecture, frameworks such as OpenAI, Anthropic, and Hugging Face, and experience with Red Teaming, adversarial testing, and data poisoning risks. You will solve complex problems regarding model security, content safety, and unintended agent behavior across multi-modal and multi-lingual contexts.
What does a Technical Program Manager earn in California?
Median $211325 from 72 postings across 20 companies.
Lead cross-functional planning and execution for the identification, selection, and execution of safety evaluations.
Manage agentic-safety evaluations including multi-turn tool calling, unsafe tool use, and unintended actions.
Translate evaluation findings into prioritized mitigation plans with assigned owners and measurable closure criteria.
Execute end-to-end safety planning for Nemotron models covering scope, dependencies, risks, and release-readiness.
Establish and track multi-turn, multi-modal, and multi-lingual evaluations across various domains and model releases.
Establish governance for reviewing safety findings, assigning severity levels, and determining release impacts.
Ensure all required safety evidence, approvals, and risk-acceptance decisions are documented before product release.
Build and maintain dashboards and executive reporting for evaluation coverage, mitigation progress, and residual risk.
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 production releases.
Familiarity with AI safety risks such as hallucinations, prompt injection attacks, unsafe tool use, data poisoning, 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 product, schedule, and release implications to leadership.