Generative AI Research Scientist: LLM Post-Training

Scale AI, Inc.; New York, Northern (NY, KY); Hybrid; USD 181,000 - 226,000; Full time

Benefits offered by this job

Health, dental and vision coverage

Retirement benefits

Learning and development stipend

Generous PTO

Commuter stipend

Job summary

Scale AI, Inc. is seeking Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) to optimize data curation and evaluation for improved LLM capabilities in text and multimodal modalities.

You will develop novel methods and collaborate with leading labs to influence the next generation of generative AI. The role emphasizes rigorous research, experimentation with bias mitigation, and dissemination of findings at major conferences and journals.

Qualifications

• 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.

Responsibilities

• Research and develop novel post-training techniques to enhance LLM core capabilities.
• 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.

Skills

Deep learning

Reinforcement learning

Large-scale fine-tuning

Research communication

Education

PhD in CS/ML

Master's in CS/ML

Tools

RLHF tooling

SFT

Preference modeling

Instruction tuning

Job description

Scale AI, Inc. is seeking Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) to optimize data curation and evaluation for improved LLM capabilities in text and multimodal modalities.

You will develop novel methods and collaborate with leading labs to influence the next generation of generative AI. The role emphasizes rigorous research, experimentation with bias mitigation, and dissemination of findings at major conferences and journals.