As the leading data and evaluation partner for frontier AI companies, Scale is dedicated to advancing the evaluation and benchmarking of large language models (LLMs). We are building industry-leading LLM evals, setting new standards for model performance assessment. Our mission is to develop rigorous, scalable, and fair evaluation methodologies to drive the next generation of AI capabilities.
Our Research teams work with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. As the Tech Lead Manager of the LLM Evals Research team, you will lead a talented team of research scientists and research engineers focused on developing and implementing novel evaluation methodologies, metrics, and benchmarks to assess the capabilities and limitations of our cutting-edge LLMs. This role is critical for designing and executing a roadmap that defines best practices in data driven AI development and will accelerate the next generation of generative AI models in partnership with top foundational model labs.
You will:
- Lead a team of highly effective research scientists and research engineers on LLM evals.
- Conduct research on the effectiveness and limitations of existing LLM evaluation techniques.
- Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness.
- Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
- Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.
- Implement scalable and reproducible evaluation pipelines using modern ML frameworks.
- Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.
- Remain up-to-date on ongoing research in the team, help work through technical challenges, and be involved in design decisions
- Remain deeply involved in the research community, both understanding trends, and setting them
- Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.
Ideally you’d have:
- 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
- Experience and track of recording in landing major research impacts in a fast-paced environment
- Experience supporting and leading a team of research scientists and research engineers
- 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.
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.