Machine Learning Research Scientist, LLM Evals

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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 a Staff Machine Learning Research Scientist on the LLM Evals team, you will lead the development of novel evaluation methodologies, metrics, and benchmarks to measure the capabilities and limitations of frontier LLMs. You will help define what "good" looks like in generative AI, driving research that informs both our internal roadmap and the broader research community.

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.

• Drive 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.
• Mentor and guide research scientists and engineers, providing technical leadership across cross‑functional projects.
• Stay deeply engaged with the ML research community, tracking emerging work and contributing to the advancement of LLM evaluation science.
• Thrive in a high‑energy, fast‑paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

• 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 producing major research impacts in a fast‑paced environment.
• Experience leading a team of research scientists and 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 for eligible roles include base salary, equity, and benefits. The range displayed on this 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.

Benefits include: comprehensive health, dental and vision coverage, retirement benefits, learning and development stipend, generous PTO, and may include a commuter stipend.

Pay range for full‑time position: $280,000—$380,000 USD.

PLEASE NOTE: Our policy requires a 90‑day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

At Scale, our mission is to develop reliable AI systems for the world’s most important decisions. Our products provide the high‑quality data and full‑stack technologies that power the world’s leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders such as Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc.,

the Government of Qatar, and U.S. government agencies including the Army and…