1 day ago
Santa Clara, CA, USAMid Level / Senior
H1B sponsor
Base Salary
$124k - $242k/yr
Responsibilities
- Develop datasets and models for training and evaluating content safety, product security, robustness, and ML fairness systems.
- Research and implement bias detection and mitigation techniques for LLMs and systems using LLMs, including RAGs.
- Define and track metrics for responsible LLM behavior and usage.
- Apply MLOps practices involving automation, monitoring, scale, and safety.
- Contribute to the MLOps platform and develop safety tools for ML teams.
- Collaborate with engineers, data scientists, and researchers on content safety and ML fairness solutions.
Requirements
- Master’s or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
- At least 2 years of experience developing and deploying machine learning models in production.
- Strong understanding of machine learning principles and algorithms.
- Hands-on Python programming experience and in-depth knowledge of machine learning frameworks such as Keras or PyTorch.
- At least 1 year of experience in content safety, ML fairness, robustness, AI model security, or a related area.
- Experience in content safety areas such as hate or harassment, sexualized content, and harmful or violent content.
- Experience working with large multimodal datasets and multimodal models.
- Preferred qualifications include LLM alignment or fine-tuning, multimodal or multilingual content safety, legal and regulatory compliance, robustness, GenAI security, scientific research, and publication experience.
Benefits
- Base salary is listed for Level 2 and Level 3, with equity and benefits also provided.
- Applications will be accepted at least until October 10, 2026.
- The posting is for an existing vacancy.
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.