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Scale Logo Scale · IT - Software Development

Machine Learning Research Scientist / Research Engineer, Post-Training

United States, San Francisco 252000.00 - 315000.00 USD / Year · Job Posted February 20, 2026
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Job Description

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models.

Job Responsibility

  • 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

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
  • 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

What we offer

  • Comprehensive health, dental and vision coverage
  • retirement benefits
  • a learning and development stipend
  • generous PTO
  • equity based compensation
  • commuter stipend
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