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Machine Learning Research Scientist Jobs (NOW HIRING)

Basis

Basis is a nonprofit applied AI research organization with two mutually reinforcing goals. The ... machine learning, computational neuroscience, cognitive science, physics, mathematics. * Excited ...

Horizon Robotics

Research Scientist

Cupertino, CA · On-site

$150K - $300K/yr

We are looking for someone with expertise in and enthusiasm for machine learning research, especially in Robotics, Embodied AI, Reinforcement learning (RL) , etc. As a Research Scientist in the team ...

Horizon Robotics

Research Scientist

Cupertino, CA · Hybrid

$150K - $300K/yr

We are looking for someone with expertise in and enthusiasm for machine learning research, especially in Robotics, Embodied AI, Reinforcement learning (RL) , etc. As a Research Scientist in the team ...

webAI

AI Research Scientist

Austin, TX · On-site

The AI Research Scientist will design, train, evaluate, and optimize cutting-edge machine learning models, collaborating with various teams to ensure innovations have real-world impact.

Apple

AIML - Machine Learning Research

Seattle, WA

$142K - $263K/yr

This involves developing sophisticated machine learning and large language models (LLMs) to ... You will also work with researchers and data scientists to develop, fine-tune, and evaluate domain ...

Roboflow

Machine Learning Research Engineer

The Machine Learning Research Engineer will develop novel methods and contribute to the research ... • Values scientific rigour, reproducibility, and high quality software • Passionate about ...

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Machine Learning Research Scientist information

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$50.5K

$130.1K

$174K

How much do machine learning research scientist jobs pay per year?

As of Sep 14, 2026, the average yearly pay for machine learning research scientist in the United States is $130,117.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What is a machine learning research scientist?

A Machine Learning Research Scientist develops new algorithms and models to advance the field of artificial intelligence. They conduct experiments, analyze data, and publish research to push the boundaries of machine learning theory and applications. Their work often involves designing novel architectures, optimizing existing models, and collaborating with engineers to bring research into production. This role typically requires a deep understanding of mathematics, statistics, and programming, along with experience in areas like deep learning, reinforcement learning, or probabilistic modeling.

What does a machine learning research scientist do?

As a Machine Learning Research Scientist, your typical projects may include developing novel algorithms, conducting experiments on large datasets, implementing and tuning models, and publishing research findings. Your daily responsibilities often involve coding, data analysis, reading the latest literature, collaborating with engineers and product teams, and participating in internal discussions about research direction. You may also mentor junior researchers, contribute to open-source projects, and present results at conferences or internal meetings. This role offers a dynamic work environment where continuous learning and innovative problem-solving are highly encouraged.

What are the key skills and qualifications needed to thrive as a machine learning research scientist?

To thrive as a Machine Learning Research Scientist, you need a strong background in mathematics, statistics, programming (typically Python or similar), and experience with machine learning frameworks, usually supported by an advanced degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Scikit-learn, and proficiency in data handling and cloud platforms is highly valued, alongside certifications like Google Cloud ML Engineer as a plus. Innovative thinking, strong communication, and effective problem-solving skills help set exceptional researchers apart. Mastery of both technical and soft skills is essential for developing impactful models, collaborating across multidisciplinary teams, and staying ahead in this fast-evolving field.

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Machine Learning Research Scientist jobs near you
Infographic showing various Machine Learning Research Scientist job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $130,117 per year, or $62.6 per hour.

Machine Learning Research Scientist, Post-Training

San Francisco, CA • On-site

Scale AI, Inc.
Software Development • 201 - 500 employees
Learn more about Scale AI, Inc.external

Other

Medical, Dental, Vision, Retirement, PTO

Posted 17 days ago

Key responsibilities

  • Research and develop novel post-training techniques such as SFT, RLHF, and reward modeling to enhance LLM capabilities.

  • Design and experiment with new approaches to preference optimization and analyze model behavior to identify weaknesses.

  • Collaborate with researchers and engineers to define best practices in data-driven AI development and contribute to the development of next-generation generative AI models.

Scale AI rating

8.5

Company rating: 8.5 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

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). 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 accommodations@scale.com. 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.

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