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Senior Machine Learning Engineer, AI Safety

NVIDIA· Engineer, Sys SW
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Hybrid (Santa Clara, CA), Hybrid (Remote (US, CA))$184k - $287.5kfull-timePosted 1mo ago

About the role

Senior ML engineer focused on AI Safety and Responsibility for Enterprise Risk Management, with emphasis on scaling safety for multi-modal LLMs and agentic safety across safety tracks including LLM Security, Frontier Risks, Agentic Safety, and Multi-turn Safety Evaluation.

Responsibilities

  • Evaluation: Develop datasets and specialized models & algorithms to evaluate/benchmark models & end-to-end systems in core safety tracks (LLM Security, Agentic Safety, Content Safety, Hallucinations, and ML Fairness).
  • Model Pre-Training, Mid-Training, Post-Training: Develop datasets and recipes for filtering training data, developing training datasets & recipes, including components like RL environments and teacher models, across core safety tracks (LLM Security, Agentic Safety, Content Safety, Hallucinations, and ML Fairness).
  • Model & system level techniques beyond post-training: Research & deploy new approaches, like Instruction Hierarchy or Risk Detection.
  • Cross-Functional Collaboration: Partner with engineers, data scientists, and research teams across NVIDIA to scale solutions for LLM Security, Agentic Safety, Content Safety, Hallucinations, and ML Fairness.

Qualifications

  • Master’s or PhD in Computer Science, Electrical Engineering, or a related quantitative field (or equivalent experience).
  • 8+ years of proven experience in systems software engineering or machine learning engineering.
  • Post-Training Experience: 4+ years of hands-on work experience in post-training of LLMs, including Supervised Fine-Tuning (SFT), Reinforcement Learning (RLHF/RLAIF), safety data generation techniques, ablation studies, and deploying models to production.
  • Core Safety Expertise: 1+ years of dedicated experience or research in at least one of the following areas: LLM Security (backdoors, poisoning, latent behaviors); Frontier Risks (deception, manipulation, loss-of-control); Agentic Safety (LLM-level risks for multi-turn tool-calling/agents); Multi-turn Safety Evaluation (dynamic and multi-turn alignment benchmarks).
  • Technical Mastery: In-depth knowledge of machine learning principles and frameworks (PyTorch preferred) with strong Python programming skills.
  • Multimodal Systems: Experience working with large multimodal datasets and multi-modal foundational models.
  • Soft Skills: Outstanding analytical problem-solving abilities paired with excellent collaboration and communication skills.
  • Cultural Alignment: Demonstrates behaviors that build trust: humility, transparency, respect, and intellectual honesty.

Skills

Required:PyTorchPython programming

Benefits

  • Equity eligible
  • Comprehensive benefits package
  • Salary range: 184,000 USD - 287,500 USD base pay annually
Last updated Oct 9, 2026. Interested? Apply on the company site.

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