Machine Learning Research Scientist / Research ...

Machine Learning Research Scientist / Research Engineer, LLM EvaluationAs 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 leaderboards, 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.We are seeking Research Scientists and Research Engineers with expertise in LLM evaluation. You will play a key role in developing and implementing novel evaluation methodologies, metrics, and benchmarks to assess the capabilities and limitations of our cutting-edge LLMs. We encourage collaborations within the industry and academia, and support the publication of research findings. Successful candidates will partner with top foundation model labs, providing both technical and strategic input on the development of the next generation of generative AI models.You will:Design and develop novel evaluation benchmarks for large language models, covering areas such as coding, instruction following, factuality, robustness, and fairness.Conduct research on the effectiveness and limitations of existing LLM evaluation techniques.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.Ideally you'd have:Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field.Strong background in deep learning and LLMs, with experience in model evaluation.Familiarity with benchmarking tools and datasets for LLM evaluation.Hands-on experience large-scale model training and deployment.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.About Us:At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI. Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We are expanding our team to accelerate the development of AI applications.We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.#J-18808-Ljbffr

Created: 2025-03-05