Machine Learning Research Scientist / Research Engineer, Post-Training

· Remote

Location

Remote

Type

Full Time

Job Description

Machine Learning Research Scientist / Research Engineer Post-Training

Reposted 19 Hours Ago
Easy Apply
3 Locations
In-Office
252K-315K Annually
Mid level
Artificial Intelligence • Big Data • Machine Learning
The Data Platform for AI: High quality training and validation data for AI applications.
The Role
The role involves developing post-training techniques for improving LLM capabilities collaborating with teams and publishing research findings.
Summary Generated by Built In

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 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.

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:
$252000$315000 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 Cisco DLA Piper 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.

Top Skills

Deep Learning
Llm
Machine Learning
Preference Optimization
Reinforcement Learning
Reward Modeling
Rlhf
Sft
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The Company
San Francisco CA
523 Employees
Year Founded: 2016

What We Do

Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR image video and NLP annotation APIs allow machine learning teams at companies like OpenAI Lyft Pinterest and Airbnb focus on building differentiated models vs. labeling data.

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Date Posted

04/03/2026

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