Machine Learning Research Scientist, Evaluations
About The Position
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) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models.
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, and with LLM evaluation or benchmark development.
- 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.
Nice To Haves
- Previous experience in a customer facing role.
Responsibilities
- Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA.
- Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities.
- Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them.
- Publish research findings in top-tier AI conferences.
Benefits
- base salary
- equity
- comprehensive health, dental and vision coverage
- retirement benefits
- a learning and development stipend
- generous PTO
- commuter stipend
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
