Agent Post-Training ML Systems Engineer for Enterprise GenAI

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

Benefits offered by this job

Health insurance

Retirement benefits

Learning stipend

Generous PTO

Commuter stipend

Job summary

Scale AI is hiring a Machine Learning Systems Research Engineer, Agent Post-training for our Enterprise GenAI team in New York. You will build, optimize, and post-train state-of-the-art models, enabling scalable agent training across enterprise use-cases, from cybersecurity to healthtech.

You will collaborate with ML engineers to run large-scale experiments, iterate on post-training recipes, and contribute to the design of next-gen multi-agent training frameworks. PhD or MS in CS preferred.

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 like 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, Flash Attention.

Responsibilities

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

Skills

LLM training

System optimization

Distributed training

Cross-functional communication

Education

PhD or Masters in Computer Science or related field

Tools

CUDA

PyTorch

Transformers

Flash Attention

Job description

Scale AI is hiring a Machine Learning Systems Research Engineer, Agent Post-training for our Enterprise GenAI team in New York. You will build, optimize, and post-train state-of-the-art models, enabling scalable agent training across enterprise use-cases, from cybersecurity to healthtech.

You will collaborate with ML engineers to run large-scale experiments, iterate on post-training recipes, and contribute to the design of next-gen multi-agent training frameworks. PhD or MS in CS preferred.