Machine Learning Engineer, AI Safety

About the Role

NVIDIA is seeking a Machine Learning Engineer focused on Product Security, Content Safety, ML Fairness, and Robustness for Large Language Models (LLMs). This role involves assessing, quantifying, and improving the safety and inclusivity of LLM models at scale.

Key Responsibilities

• Develop datasets and models for training and evaluating models and end-to-end systems for Content Safety, ProdSec, Robustness, and ML Fairness.
• Research and implement cutting-edge techniques for bias detection and mitigation in LLMs and systems using LLMs like RAGs.
• Define and track key metrics for responsible LLM behavior and usage.
• Follow best MLOps practices for automation, monitoring, scale, and safety.
• Contribute to the MLOps platform and develop safety tools to enhance ML team effectiveness.
• Collaborate with engineers, data scientists, and researchers to implement solutions for content safety and ML fairness challenges.

Requirements & Tech Stack

• Minimum of 2+ years of work experience in developing and deploying machine learning models in production.
• Strong understanding of machine learning principles and algorithms.
• Hands-on programming experience in python.
• In-depth knowledge of machine learning frameworks, like Keras or PyTorch.
• Background in one or more of the following for 1+ years: Content Safety, ML Fairness, Robustness, AI Model Security, or related areas.
• Experience working with large multi-modal datasets and multi-modal models.
• Good problem-solving and analytical abilities.
• Excellent collaboration and communication skills.
• Demonstrates behaviors that build trust: humility, transparency, respect, and intellectual honesty.

Qualifications

• Master’s or PhD in Computer Science, Electrical Engineering, or related field - or equivalent experience.
• Experience working in a range of the following areas within Content Safety: Hate/Harassment, Sexualized, Harmful/Violent, or other specific areas from your application.

Ways To Stand Out From The Crowd

• Skilled with alignment/fine-tuning of LLMs - including regular LLMs as well as VLMs (vision-language models) or any-to-text.
• Proven experience with multimodal and/or multilingual content safety, legal, and regulatory compliance.
• Knowledge of robustness, including hallucinations, digressions, and generative misinformation.
• Experience with GenAI security, including prompt stability, model extraction, confidentiality/data extraction, integrity, availability, and adversarial robustness.
• Passion for AI and a demonstrated commitment to advancing the field through innovative research, prior scientific research, and publication experience.