Machine Learning Systems Research Engineer (Enterprise GenAI)

TL;DR

Machine Learning Systems Research Engineer (Enterprise GenAI): Develop and optimize post-training algorithms and training frameworks for next-generation enterprise AI agents with an accent on large-scale LLM training, system optimization, and multi-agent training algorithms. Focus on building stable post-training recipes, supporting multi-node GPU clusters, and integrating state-of-the-art ML technologies.

Location: San Francisco, CA or New York, NY, USA (onsite)

Salary: $180,600–$315,000 USD

Company

Scale AI accelerates AI development by providing high-quality data and full-stack technologies powering leading AI models for enterprises and governments worldwide.

What you will do

• Build, profile, and optimize training and inference frameworks for large-scale ML systems.
• Post-train state-of-the-art models to define stable post-training recipes for enterprise use cases.
• Collaborate with ML teams to accelerate research and enable next-generation model and data curation.
• Create next-gen agent training algorithms for multi-agent and multi-tool rollouts.

Requirements

• Location: Must be onsite in San Francisco, CA or New York, NY, USA
• 1-3 years of LLM training experience in production environments.
• Experience with post-training methods such as RLHF, RLVR, PPO, GRPO.
• Strong software engineering skills with CUDA, PyTorch, transformers, and GPU cluster operation.
• PhD or Masters in Computer Science or related field.
• Strong communication skills for cross-functional collaboration.

Culture & Benefits

• Comprehensive health, dental, and vision coverage.
• Retirement benefits and equity compensation.
• Learning and development stipend.
• Generous paid time off and commuter stipend.
• Inclusive and equal opportunity workplace with accommodations for disabilities.