Nvidia is looking for a talented Deep Learning Scientist to work on Product Security, Content Safety, ML Fairness and Hallucinations efforts for LLMs across all of our research and production engineering teams. In this role you’ll have the opportunity to take on innovative problems in machine learning, particularly focused on safety for multi-lingual LLMs, including with multi-modal and multi-turn and reasoning. This role is directed at assessing, and improving the safety and inclusivity of our LLM models in a scalable fashion. Our LLMs are a growing area of AI products including models, datasets and services, and we are committed to ensuring that they are used safely and responsibly.
NVIDIA is in a unique position: we are developing AI-based products across multiple domains and we collaborate with many interesting AI companies as partners and customers. Ensuring the highest Content Safety possible reduces exposure to inappropriate material. Preventing Bias and Discrimination is essential to both protect individual rights and to achieve the best quality of results including accuracy and completeness of information. By prioritizing content safety and fairness, we can ensure that LLMs benefit everyone and contribute to a better future for all.
What you'll be doing:
- Develop datasets and moderator models for evaluating LLM models and end-to-end systems for Content Safety, ML Fairness. These LLM models can be txt-to-txt or multimodal-to-txt.
- Develop datasets for training LLM models with SFT and RL techniques, for Content Safety, ML Fairness, Security and more.
- Research and implement cutting-edge techniques for bias detection and mitigation in LLMs and systems.
- Define and track key metrics for responsible LLM behavior and usage.
- Follow the best practices of automation, monitoring, scale, safety.
- Contribute to our repositories 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 have equivalent experience.
- 5+ 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.
- 2+ years of work experience with one or more of the following broader areas for 2+ years: Content Safety, ML Fairness, AI Model Security, or related areas.
- Experience 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-lingual datasets and multi-lingual 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:
- Experience with alignment/fine-tuning of LLMs - including regular LLMs as well as VLMs (Vision Language Model) or any-to-text
- Prior experience with multimodal and/or multilingual Content Safety, legal and regulatory compliance.
- Experience with Hallucinations/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.
With highly competitive salaries and a comprehensive benefits package, Nvidia is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working with us and our engineering teams are growing fast in some of the hottest state of the art fields: Deep Learning, Artificial Intelligence, and Large Language Models. If you're a creative engineer with a real passion for robust and enjoyable user experiences, we want to hear from you.
NVIDIA is committed to encouraging a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.