Senior AI Safety Engineer - Equity & Agentic Automation

NVIDIA Corporation; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits package

Competitive salary

Job summary

NVIDIA is seeking a senior ML/AI systems engineer to architect agentic automation loops, build safety and optimization models, and guide auto-research frameworks. You will work across safety evaluations, model testing, and production pipelines, using Rust or Python and PyTorch to deliver scalable solutions.

You will collaborate with researchers, platform engineers, and data scientists to bridge theoretical safety research with practical, automated systems, while contributing to cutting-edge AI

Qualifications

• Bachelor's or Master's in Computer Science, Machine Learning, Software Engineering, or related field.
• 8+ years of experience in ML engineering or software engineering.
• Agentic systems & automation with LLMs, multi-turn tool-calling, orchestration, and autonomous agent loops; strong proficiency in Rust or Python; PyTorch required.
• Demonstrated ability to tackle open-ended, ambiguous problems and own projects end-to-end.

Responsibilities

• Architect agentic automation loops spanning safety evaluations, red-teaming, model testing, post-training and ablations.
• Develop safety models for identifying harmful content and run-time guardrails.
• Pioneer auto-research frameworks using LLMs and autonomous agents to discover vulnerabilities and generate datasets.
• Scale innovative interventions into robust production-ready systems.

Skills

LLM orchestration

Python

Rust

ML engineering

Systems design

Education

Bachelor's degree in Computer Science or related field

Master's degree in Computer Science or related field

Tools

PyTorch

LangChain

AutoGPT

Semantic Kernel

Job description

NVIDIA is seeking a senior ML/AI systems engineer to architect agentic automation loops, build safety and optimization models, and guide auto-research frameworks. You will work across safety evaluations, model testing, and production pipelines, using Rust or Python and PyTorch to deliver scalable solutions.

You will collaborate with researchers, platform engineers, and data scientists to bridge theoretical safety research with practical, automated systems, while contributing to cutting-edge AI