Machine Learning Engineer, AI Safety
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Job Description
Machine Learning Engineer at NVIDIA developing AI-based products focusing on safety and fairness in LLMs. Responsible for addressing challenges in Content Safety, ProdSec, Robustness and ML Fairness across teams.
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
Requirements:
- 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 the following 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.
Benefits:
- Equity
- Comprehensive benefits package
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