Senior Machine Learning Engineer, AI Safety

🕒 August 31

🏄 California – Remote

🏄 California – Remote

💵 $184k - $287.5k / year

⏰ Full Time

🟠 Senior

🤖 AI Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 14%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Develop datasets, specialized models, and algorithms to evaluate and benchmark models and end-to-end systems across LLM Security, Agentic Safety, Content Safety, Hallucinations, and ML Fairness • Develop datasets and training recipes for model pre-training, mid-training, and post-training, including RL environments and teacher models • Research and deploy techniques beyond post-training, such as Instruction Hierarchy and Risk Detection • Partner with engineers, data scientists, and research teams across NVIDIA to scale AI safety solutions • Focus on measuring and improving security, content safety, and inclusivity of frontier multimodal models

🎯 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 post-training experience with LLMs, including SFT, RLHF/RLAIF, safety data generation techniques, ablation studies, and production deployment • 1+ years of dedicated experience or research in LLM Security, Frontier Risks, Agentic Safety, or Multi-turn Safety Evaluation • In-depth knowledge of machine learning principles and frameworks, with PyTorch preferred • Strong Python programming skills • Experience with large multimodal datasets and multimodal foundational models • Outstanding analytical problem-solving abilities and excellent collaboration and communication skills • Behaviors that build trust: humility, transparency, respect, and intellectual honesty

🏖️ Benefits

• Equity • Comprehensive benefits package • Equal opportunity and inclusive work environment