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Machine Learning Engineer, AI Safety

NVIDIA· Engineer, Sys SW
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Hybrid (Santa Clara, CA), Remote$124k - $195.5kFull-timePosted 2mo ago

About the role

ML Engineer focused on Product Security, Content Safety, ML Fairness and Robustness for LLMs across research and production teams, with emphasis on safety for multi-modal models and scalable assessment of safety and inclusivity.

Responsibilities

  • Develop the 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 the best MLOps practices of automation, monitoring, scale and safety.
  • Contribute to the MLOps platform and develop safety tools to help ML teams be more effective.
  • Collaborate with other engineers, data scientists, and researchers to develop and implement solutions to content safety and ML fairness challenges.

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 machine learning frameworks, like Keras or PyTorch.
  • Background in one or more of the following broader areas for 1+ years: Content Safety, ML Fairness, Robustness, AI Model Security, or related areas.
  • Experience working in a range of areas within Content Safety: Hate/Harassment, Sexualized, Harmful/Violent, or other specific areas from your application.
  • Practice working with large multi-modal datasets and multi-modal models.
  • Good at problem-solving and analytical ability.
  • Excellent collaboration and communication skills.
  • Demonstrates behaviors that build trust: humility, transparency, respect, and intellectual honesty.

Skills

Required:Datasets and models for safety evaluationBias detection and mitigation in LLMsMLOps practicesPythonPyTorch/Keras

Benefits

  • equity and benefits
Last updated Oct 9, 2026. Interested? Apply on the company site.

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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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