Machine Learning Research Scientist / Research Engineer, Post-Training

Scale AI; New York, San Francisco (IA, CA); On-site; USD 176,000 - 255,000; Full time

Job summary

An innovative company is seeking a Machine Learning Research Scientist to advance generative AI research. This role focuses on post-training techniques, including SFT and RLHF, to optimize large-scale models. Collaborating with top AI labs, you will contribute to improving instruction following, factuality, and multilingual understanding. This position offers a dynamic environment where your research can shape the future of AI technologies. If you are passionate about AI and eager to make a significant impact, this is the opportunity for you.

Qualifications

• Ph.D. or Master's degree in Computer Science, Machine Learning, or related field.
• Deep understanding of deep learning and reinforcement learning.

Responsibilities

• Develop novel post-training techniques to enhance LLM capabilities.
• Analyze model behavior and propose solutions for bias mitigation.

Skills

Deep Learning

Reinforcement Learning

Large-Scale Model Fine-Tuning

Bias Mitigation

Excellent Communication Skills

Education

Ph.D. in Computer Science

Master's in Machine Learning

Job description

Machine Learning Research Scientist / Research Engineer, Post-Training

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 algorithmic improvements to enhance LLM capabilities in core areas such as instruction following, factuality, coding, multilingual and multimodal understanding.

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 areas of instruction following, factuality, coding, multilingual and multimodal understanding.
• 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:

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.

Location:

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:

$176,000 - $255,000 USD

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, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI. Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. 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 affirmative action employer and 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 [e-mail].