Nvidia Machine Learning Engineer AI Safety - LLM MLOps 

United States, Texas 

720639075

What you'll be doing:

• Develop the datasets and models for training and evaluating models and end-to-end systems for Content Safety 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, 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.

What we need to see:

• You have a Master’s or PhD in Computer Science, Electrical Engineering or related field or equivalent experience.

• 3+ 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.

• Experience with one or more of the following broader areas for 2+ years: Content Safety, ML Fairness, Robustness, AI Model Security, or related areas.

• Background with one or more of the following areas within Content Safety: Hate/Harassment, Sexualized, Harmful/Violent, or other specific areas from your application.

• Experience 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, intellectual honesty.

Ways to stand out from the crowd:

• Background withalignment/fine-tuningof LLMs - including regular LLMs as well as VLMs (Vision Language Model) or any-to-text

• Experience with multimodal and/or multilingual Content Safety, legal and regulatory compliance.

• Background with Robustness including Hallucinations, Digressions, 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.