ML Safety Engineer for Multimodal LLMs with Equity

NVIDIA; California (MO); On-site; USD 124,000 - 241,500; Full time

Benefits offered by this job

Equity

Benefits package

Job summary

NVIDIA seeks a talented Machine Learning Engineer to advance Product Security, Content Safety, ML Fairness and Robustness for LLMs across research and production teams. You will address safety, bias, and inclusivity in multi-modal models with scalable solutions.

Ideal candidates bring 2+ years of production ML experience, strong Python and PyTorch/Keras skills, and a background in content safety or related areas.

Qualifications

• Master’s or PhD in Computer Science, Electrical Engineering or related field or equivalent experience.
• 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 and in-depth knowledge of ML frameworks like PyTorch or Keras.
• Background in Content Safety, ML Fairness, Robustness, or AI Model Security.

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 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 of automation, monitoring, scale and safety.
• Collaborate with engineers, data scientists and researchers to address content safety and ML fairness challenges.

Skills

Python

ML frameworks (PyTorch/Keras)

Multimodal ML

Content Safety & ML Fairness

Model security / GenAI security

Problem solving

Collaboration & Communication

Education

Master’s or PhD in Computer Science, Electrical Engineering or related field

Tools

PyTorch

Keras

Job description

NVIDIA seeks a talented Machine Learning Engineer to advance Product Security, Content Safety, ML Fairness and Robustness for LLMs across research and production teams. You will address safety, bias, and inclusivity in multi-modal models with scalable solutions.

Ideal candidates bring 2+ years of production ML experience, strong Python and PyTorch/Keras skills, and a background in content safety or related areas.