Scale AI

Machine Learning Research Scientist, Evaluations

Scale AI$180K — $225K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Ph.D. or Master's in Computer Science, Machine Learning, AI, or related field
  • Deep knowledge of deep learning, reinforcement learning, and fine-tuning large models
  • Experience with post-training techniques like RLHF and instruction tuning
  • Proven track record in LLM evaluation or benchmark development
  • Strong written and verbal communication skills
  • Published research at major AI conferences or journals

Responsibilities

  • Analyze model behavior to uncover and diagnose failure modes in frontier LLMs and Agents
  • Design and construct benchmarks to evaluate LLMs in text and multimodal settings
  • Apply expertise in post-training methods to link failures to data and training interventions
  • Collaborate with teams to set evaluation best practices in AI development
  • Publish findings in top-tier AI research conferences

Benefits

  • Comprehensive health, dental, and vision coverage
  • Retirement benefits
  • Learning and development stipend
  • Generous paid time off (PTO)
  • Potential commuter stipend
Full Job Description
Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities.

In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models.

You will:
  • Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You'll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA.
  • Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities.
  • Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them.
  • Publish research findings in top-tier AI conferences.

Ideally you'd have:
  • 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, and with LLM evaluation or benchmark development.
  • 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 and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, 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.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$180,600-$225,750 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.

About Scale AI

Scale AI is an artificial intelligence company that provides data annotation services to improve machine learning algorithms. The company's platform offers a range of services including image annotation, text annotation, and 3D annotation. Scale AI was founded in 2016 and is headquartered in San Francisco, California.
Learn more about Scale AI
Size
500 employees
Industry
Founded
2017

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