Machine Learning Research Scientist, Post-Training
Company websitescale.com (Scale AI, opens in new tab)
Base salary $165,600 to $207,000
Employer-published annual base salary, USD. Advertised base range in San Francisco, CA +2 more
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSan Francisco, CA +2 more
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (2 h ago) · observed since
All places named
- San Francisco, CA
- New York, NY
- Seattle, WA
About this job
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). 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.
You will:
- 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.
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.
- 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:
$165,600—$207,000 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.
About Us:
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 like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. 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.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.
We comply with the United States Department of Labor's Pay Transparency provision.
PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Source: Scale AI on Greenhouse · View original posting (opens in new tab)
This listingMachine Learning Research Scientist, Post-Training$165,600 to $207,000
Machine Learning Research Scientist, Evaluations$165,600 to $207,000
Finance Systems Integration Lead$165,600 to $207,000
Engagement Manager (Hawaii), Public Sector$166,400 to $249,000
Engagement Manager, Public Sector$166,400 to $249,000
Engagement Manager (Homeland Layered Defense), Public Sector$166,400 to $208,000
Technical Program Manager, Public Sector$166,400 to $249,000
Chart as a table
| Role | Published base |
|---|---|
| Machine Learning Research Scientist, Post-Training (this listing) | $165,600 - $207,000 |
| Machine Learning Research Scientist, Evaluations | $165,600 - $207,000 |
| Finance Systems Integration Lead | $165,600 - $207,000 |
| Engagement Manager (Hawaii), Public Sector | $166,400 - $249,000 |
| Engagement Manager, Public Sector | $166,400 - $249,000 |
| Engagement Manager (Homeland Layered Defense), Public Sector | $166,400 - $208,000 |
| Technical Program Manager, Public Sector | $166,400 - $249,000 |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2025-02-11
Where this pay comes from
Location as the employer wrote it: 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:
USD 165,600 – 207,000 · interval unstated · pay_input_range · 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: · base-labelled (R1: base salary)
- Method
- Structured pay field published by the employer
- Checked
- Rule set
- us-base-v2
The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
