Machine Learning Systems Research Engineer, Agent Post-training - Enterprise GenAI

About the role

At Scale, our mission is to accelerate the development of AI applications. For 9 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent investment from Meta, we are doubling down on building state-of-the-art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world.

The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research and resources that serve all of our enterprise clients. As an ML Sys Research Engineer, you’ll work on building out the algorithms for our next-gen Agent RL training platform, support large-scale training, and research and integrate state-of-the-art technologies to optimize our ML system. Your customers will be other MLREs and AAIs on the Enterprise AI team who are applying the training algorithms to client use-cases ranging from next-generation AI cybersecurity firewall LLMs to training foundation healthtech search models.

Responsibilities

• Build, profile, and optimize our training and inference framework.
• Post-train state-of-the-art models, developed both internally and from the community, to define stable post-training recipes for our enterprise engagements.
• Collaborate with ML teams to accelerate their research and development, enabling them to develop the next generation of models and data curation.
• Create a next-gen agent training algorithm for multi-agent/multi-tool rollouts.

Requirements

• At least 1-3 years of LLM training in a production environment.
• Passionate about system optimization.
• Experience with post-training methods like RLHF/RLVR and related algorithms such as PPO/GRPO.
• Ability to demonstrate know-how in operating the architecture of modern GPU clusters.
• Experience with multi-node LLM training and inference.
• Strong software engineering skills, proficient in frameworks and tools such as CUDA, PyTorch, transformers, flash attention, etc.
• Strong written and verbal communication skills to operate in a cross-functional team environment.
• PhD or Masters in Computer Science or a related field.

Benefits

• Comprehensive health, dental, and vision coverage.
• Retirement benefits.
• A learning and development stipend.
• Generous PTO.
• Eligibility for additional benefits such as a commuter stipend.

Pay

The base salary range for this full-time position in San Francisco, New York, or Seattle is $264,800—$331,000 USD.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed reflects the minimum and maximum target for new hire salaries and may include 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.