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

About the role

The Enterprise ML Research Lab works on the front lines of the AI revolution. We are developing an arsenal of proprietary research and resources to 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.

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, and enable 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 like PPO/GRPO etc.
• Ability to demonstrate know-how on how to operate the architecture of the modern GPU cluster
• 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

Qualifications

Ideal candidates will have:

• PhD or Masters in Computer Science or a related field
• Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
• 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.

Skills

• Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
• 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.

Benefits

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.

Pay

$264,800 - $331,000 USD

Schedule

Full-time