The opportunity
Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling).
What you'll do
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.
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.
What they're looking for
- 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.
