Machine Learning Engineer, AI Safety

Thomas To; Santa Clara (CA); Presencial; USD 124.000 - 242.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Equity

Comprehensive benefits

Competitive salary

Descripción de la vacante

NVIDIA is hiring a research-focused ML engineer to develop datasets and models for training and evaluating models across Content Safety, ProdSec, Robustness, and ML Fairness. You will implement bias mitigation techniques and track responsible-LLM metrics, while following MLOps best practices to automate, monitor, and scale systems.

You will collaborate with engineers, data scientists, and researchers to tackle content safety and ML fairness challenges, with opportunities to work on multimodal

Formación

• 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 ML frameworks like PyTorch or Keras.
• Background in Content Safety, ML Fairness, Robustness, AI Model Security or related areas.

Responsabilidades

• Develop 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.

Conocimientos

Python

ML frameworks

Problem-solving

Collaboration

Communication

Educación

Master's or PhD in CS/EE or related

2+ years ML production experience

Herramientas

PyTorch

Keras

Multimodal datasets/tools

Descripción del empleo

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 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, 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.

What We Need To See

• 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.

Ways To Stand Out From The Crowd

• Skilled with alignment/fine‑tuning of LLMs - including regular LLMs as well as VLMs (vision‑language models) or any‑to‑text
• Proven experience with multimodal and/or multilingual content safety, legal, and regulatory compliance.
• Knowledge of robustness, including hallucinations, digressions, and 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.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 10, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.