Machine Learning Research Scientist, Post-Training

Scale AI
San Francisco, Seattle, New York
Workplace: OnsiteFull timeUSD 252,000 - 315,000 annuallyFunction: Data Science & Machine LearningSkills: ["Communication","Collaboration"]

We are seeking Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) to optimize data curation and evaluation for improving LLMs across text and multimodal modalities. You will develop methods to improve alignment and generalization, collaborate with researchers and engineers, and contribute to cutting-edge generative AI research and practice.

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FursaFursa
Scale AI
Scale AI
1 year ago

Machine Learning Research Scientist, Post-Training

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 14 hours agoStatus: Live

Job Summary

We are seeking Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) to optimize data curation and evaluation for improving LLMs across text and multimodal modalities. You will develop methods to improve alignment and generalization, collaborate with researchers and engineers, and contribute to cutting-edge generative AI research and practice.
Location: San Francisco, Seattle, New York
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •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.

Pay and Benefits

Salary: USD 252,000 - 315,000 annually
Perks:Health InsuranceDentalVisionRetirement BenefitsLearning StipendPaid LeaveCommuter Benefits

Key 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
Experience:Artificial intelligenceMachine learningGen aiLLM
Skills:CommunicationCollaboration
Languages:English
Tech Stack:RLHFSFTReward modelingDeep learningReinforcement learningInstruction tuningLarge language modelsLLM

Company Brief

Scale AI
Provides data labeling, annotation, and infrastructure services to accelerate machine learning and AI development. Supplies high-quality training data, tooling, and APIs for customers in autonomous vehicles, mapping, robotics, and enterprise AI applications.
Industry: AI & Machine Learning
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2016
WebsiteLinkedIn