Machine Learning Research Scientist, Post-Training

About the Position

Machine Learning Research Scientist, Post-Training

Scale AI is seeking a Machine Learning Research Scientist, Post-Training to optimize data curation and enhance LLM capabilities in text and multimodal modalities.

Responsibilities

• Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities.
• Design and experiment new approaches to preference optimization.
• Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness.
• Publish research findings in top-tier AI conferences.

Requirements

• Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field.
• Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning.
• Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning.
• Excellent written and verbal communication skills.
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals.
• Previous experience in a customer-facing role.

We Offer

• Competitive salary: $180k – $225k
• Job Locations: New York City, Seattle, San Francisco
• Full-time employment

About the Company

Scale AI

Scale AI is a rapidly growing enterprise software company specializing in Machine Learning and Artificial Intelligence. With a valuation of $1B or more, Scale AI has received significant investment from top investors and is backed by Y Combinator.

Perks

• Healthcare benefits: Health, dental & vision coverage
• 401(K) via Guideline
• Parental leave
• Equity benefits
• Work from home policy
• Generous paid time off
• Company meals: Free lunch and dinner
• Commuter benefits
• Company events: Regular social activities
• Flexible work hours

More Information

Learn more about Scale AI and explore other job opportunities here.