# Senior Machine Learning Engineer, AI Safety

**Company**: NVIDIA
**Location**: Santa Clara, CA
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Machine-Learning-Engineer--AI-Safety_JR2024679?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_b2ebc3cf-14c

## Description

NVIDIA is seeking a Senior Machine Learning Engineer to join its AI Safety and Responsibility efforts for Enterprise Risk Management. You will work on innovative problems in machine learning, focusing on scaling safety for multi-modal Large Language Models (LLMs) including advanced agentic safety.

The role involves measuring and improving the security, content safety, and inclusivity of frontier models. Key areas of focus include:

- LLM Security: backdoors, data poisoning, latent malicious behavior, and structural model vulnerabilities

- Frontier Risks: advanced alignment challenges, including model deception, manipulation, and loss-of-control scenarios

- Agentic Safety: LLM-level safety for autonomous systems, including multi-turn tool-calling, orchestration, and execution risks

- Multi-turn Safety Evaluation: robust, scalable automated evaluation methodologies for conversational and iterative multi-turn use cases

Responsibilities:

- 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)

- Develop datasets and recipes for filtering training data, developing training datasets & recipes, including components like RL environments and teacher models, across core safety tracks

- Research & deploy new approaches, like Instruction Hierarchy or Risk Detection

- Partner 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 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

- 1+ years of dedicated experience or research in at least one of the following areas: LLM Security, Frontier Risks, Agentic Safety, 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:

- Highly competitive salaries

- Comprehensive benefits package

- Equity eligibility

## Skills

### Required
- Machine Learning
- Deep Learning
- Large Language Models
- AI Safety
- Python
- PyTorch

### Nice to have
- Published papers on AI Safety
- Contributions to open-source AI Safety tools
- Experience with alignment/fine-tuning of Vision-Language Models

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Machine-Learning-Engineer--AI-Safety_JR2024679?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)