Senior Machine Learning Engineer, AI Safety

$184k - $288k • Remote • US, CA, Santa Clara

Posted 13d ago

Job Location

US, CA, Santa Clara

Tech Stack

Python LLM Fine-Tuning PyTorch Reinforcement Learning Deep Learning RLHF Machine Learning AI safety Foundation Models multimodal systems Agentic Safety

Remote Work Policy

Fully remote

About the job

NVIDIA is seeking talented Deep Learning Scientists, AI Researchers, and Machine Learning Engineers to join our AI Safety and Responsibility efforts for Enterprise Risk Management. This role focuses on scaling safety for multi-modal Large Language Models (LLMs), including advanced agentic safety, and measuring/improving the security, content safety, and inclusivity of frontier models. You will tackle innovative problems in machine learning, collaborating with world-leading AI companies and internal teams.

Responsibilities

Develop datasets and specialized models/algorithms to evaluate and benchmark models and end-to-end systems in core safety tracks (LLM Security, Agentic Safety, Content Safety, Hallucinations, ML Fairness).
Develop datasets and recipes for filtering training data and creating training datasets, including RL environments and teacher models, across core safety tracks.
Research and deploy new model and system-level techniques beyond post-training, such as Instruction Hierarchy or Risk Detection.
Collaborate with engineers, data scientists, and research teams across NVIDIA to scale solutions for LLM Security, Agentic Safety, Content Safety, Hallucinations, and ML Fairness.

Requirements

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.
4+ years of hands-on experience in post-training of LLMs, including SFT, RLHF/RLAIF, safety data generation, ablation studies, and deploying models to production.
1+ years of dedicated experience or research in at least one of the following areas: LLM Security, Frontier Risks, Agentic Safety, or Multi-turn Safety Evaluation.
In-depth knowledge of machine learning principles and frameworks (PyTorch preferred) with strong Python programming skills.
Experience working with large multimodal datasets and multi-modal foundational models.
Outstanding analytical problem-solving abilities paired with excellent collaboration and communication skills.
Demonstrates behaviors that build trust: humility, transparency, respect, and intellectual honesty.

Benefits

Equity
Comprehensive benefits package

About nvidia

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