Enterprise ML Systems Research Engineer - GenAI & Agent

Scale AI; San Francisco (CA); On-site; USD 265,000 - 331,000; Full time

Benefits offered by this job

Health, dental and vision coverage

Equity compensation

Learning and development stipend

Generous PTO

Commuter stipend

Job summary

Scale AI in San Francisco is seeking an ML Systems Research Engineer/Scientist to build and optimize post-training workflows for large language models. You will train, evaluate, and integrate state-of-the-art algorithms to support enterprise AI use cases across security, healthtech, and data curation.

You’ll collaborate with ML teams to accelerate research, profile performance on multi-node GPU clusters, and contribute to next-generation agent training platforms.

Qualifications

• 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 (PPO/GRPO).
• Ability to operate the architecture of a modern GPU cluster.
• Experience with multi-node LLM training and inference.
• Strong software engineering skills with CUDA, PyTorch, Transformers, and related tools.
• Strong written and verbal communication in a cross-functional team.
• PhD or MSc in Computer Science or related field.

Responsibilities

• Build, profile and optimize our training and inference framework.
• Post-train state-of-the-art models to define recipes for enterprise engagements.
• Collaborate with ML teams to accelerate research and development.
• Create a next-gen agent training algorithm for multi-agent/multi-tool rollouts.

Skills

LLM training

System optimization

Multi-node training

Communication skills

Education

PhD or MSc in CS

Tools

CUDA

PyTorch

Transformers

Flash attention

Job description

Scale AI in San Francisco is seeking an ML Systems Research Engineer/Scientist to build and optimize post-training workflows for large language models. You will train, evaluate, and integrate state-of-the-art algorithms to support enterprise AI use cases across security, healthtech, and data curation.

You’ll collaborate with ML teams to accelerate research, profile performance on multi-node GPU clusters, and contribute to next-generation agent training platforms.