Senior AI Safety & ML Program Manager

NVIDIA; Santa Clara (CA); On-site; USD 168,000 - 322,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA in Santa Clara, CA, is seeking a Senior Technical Program Manager to lead safety-focused programs at the frontier of AI. You will coordinate cross-functional planning and execution for evaluating agentic-safety features, tracking results, and translating findings into actionable mitigation plans with owners and dates.

You will drive end-to-end safety programs for Nemotron models, align priorities to LLM security, and establish governance for safety findings, release impact, and risk

Qualifications

• 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.

Responsibilities

• Lead cross-functional planning and execution for evaluation identification, selection and execution. With a focus on agentic-safety evaluations, including multi-turn tool calling, unsafe tool use, unintended actions, excessive autonomy, and multi-step failures.
• Track execution, results for all evals, analysis, and the mitigation and research plans for improvement that will stem from results analysis. Translate evaluation findings into prioritized mitigation plans with accountable owners, committed dates, and measurable closure criteria
• Lead end-to-end safety planning and execution for Nemotron models, including program scope, dependencies, risks, resources, and release-readiness criteria.
• Translate technical safety priorities into executable programs covering LLM security, frontier risks, agentic safety, hallucinations
• Establish and track multi-turn, multi-modal, multi-lingual, long-context, and reasoning model evaluations across relevant use cases, domains, languages, modalities, and model releases.
• Establish governance for reviewing safety findings, assigning severity, determining release impact, and escalating unresolved risks. Ensure required safety evidence, approvals, exceptions, and risk-acceptance decisions are documented before release. Identify program gaps and critical dependencies early and drive decisions, escalations, recovery plans, and corrective actions.
• Build (with AI for Code/AI for Work) and maintain dashboards and executive reporting for evaluation coverage, critical findings, mitigation progress, residual risk, and release readiness.

Skills

Technical program management

LLM architecture

LLM frameworks

Model evaluation

Tool calling

AI safety risks

Red Teaming

Adversarial testing

Stakeholder communication

Education

Bachelor’s degree or equivalent experience in computer science, engineering, data science, or a related technical field

Job description

NVIDIA in Santa Clara, CA, is seeking a Senior Technical Program Manager to lead safety-focused programs at the frontier of AI. You will coordinate cross-functional planning and execution for evaluating agentic-safety features, tracking results, and translating findings into actionable mitigation plans with owners and dates.

You will drive end-to-end safety programs for Nemotron models, align priorities to LLM security, and establish governance for safety findings, release impact, and risk