Machine Learning Research Engineer, Agents - Enterprise GenAI

Overview

The Enterprise ML Research Lab at Scale is dedicated to advancing AI applications across various sectors. With recent investments from Meta, we are focusing on developing state-of-the-art post-training algorithms to support complex agents in enterprises worldwide. As an Agent MLRE, you will contribute to creating best-in-class Agents that achieve superior performance through a blend of internal and community-developed models.

Responsibilities

• Train state-of-the-art models, both internally and from the community, to deploy to enterprise customers.
• Research cutting-edge algorithms to integrate directly into our training stack.
• Create agents that leverage proprietary agent-building algorithms to automatically optimize datasets, including defining tools, multi-agent systems, and complex rewards.

Requirements

• 1-3 years of experience building with Large Language Models (LLMs) in a production environment.
• Publications in top-tier conferences such as NEURIPS, ICLR, or ICML within the past two years.
• A PhD or Master’s degree in Computer Science or a related field.

Qualifications

• Strong background in machine learning, reinforcement learning, and deep learning.
• Experience with reinforcement learning frameworks like PPO, GRPO, and RLHF.
• Ability to analyze and interpret complex datasets to improve model performance.

Benefits

• Comprehensive health, dental, and vision coverage.
• Roth IRA matching.
• Learning and development stipend.
• Generous paid time off.

Pay

• Base salary range: $264,800—$331,000 USD for full-time positions in San Francisco, New York, and Seattle.

Schedule

• Full-time position.

Benefits

• Retirement benefits.
• Commute stipend (if applicable).

Equal Opportunity Employer

Scale is committed to fostering an inclusive and equal opportunity workplace. We are dedicated to providing reasonable accommodations to applicants with disabilities. For more information, please refer to our Equal Employment Opportunity statement and our privacy policy.