AI Safety Machine Learning Engineer, LLM MLOps

Posted 2 Days Ago
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Santa Clara, CA
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
As an AI Safety Machine Learning Engineer at NVIDIA, you'll develop datasets and models for Content Safety and ML Fairness, implement bias detection techniques, and collaborate with teams on safety and fairness challenges in LLMs. Your work will focus on assessing and improving the safety of AI products.
Summary Generated by Built In

Join NVIDIA as a Machine Learning Engineer and contribute to Product Security, Content Safety, ML Fairness, and Robustness efforts for LLMs in 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-modal LLMs. This role is directed at assessing, quantifying, and improving the safety and inclusivity of our LLM models in a scalable fashion. Our team also works in the area of safety for generative models for language, robustness, and explainability. Our LLMs are a growing area of AI products including models 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 safety and fairness, we can ensure that LLMs benefit everyone and contribute to a better future for all.

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, fairness.

  • Contribute to the MLOps platform and develop safety and fairness 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.

  • 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.

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

  • Background working with large multi-modal datasets and multi-modal models.

  • Passion for Content Safety.

  • Good at problem solving and analytical ability with 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

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

  • Experience 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.

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.

The base salary range is 148,000 USD - 287,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering 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.

Top Skills

Python
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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