GenAI Agent ML Scientist — Post-Training & RL Lead

Scale AI, Inc.; New York (NY); On-site; USD 265,000 - 331,000; Full time

Benefits offered by this job

Equity compensation

Health, dental, vision benefits

Learning & development stipend

Paid time off (PTO)

Commuter stipend

Job summary

Scale AI, Inc. is seeking a Machine Learning Research Scientist for Enterprise GenAI to advance RL-based agent systems and post-training techniques in real-world datasets.

You will train state-of-the-art models for enterprise customers and contribute novel algorithms to our training stack, delivering high-impact agents with robust rewards and tooling. The role emphasizes cutting-edge research, publication in top venues, and collaboration with a global team in a dynamic GenAI environment.

Qualifications

• 1–3 years of building with LLMs in production environments.
• Experience with post-training methods like RLHF/RLVR and related algorithms such as PPO/GRPO.
• Publications in NEURIPS, ICLR, or ICML in the last two years.
• PhD or Master's degree in Computer Science or a related field.

Responsibilities

• Train state-of-the-art models, internally developed or from the community, for enterprise customers.
• Research cutting-edge algorithms to integrate into Scale's training stack.
• Build agents using proprietary agent-building algorithms to optimize datasets, including defining high-performing tools, multi-agent systems, and complex rewards.

Skills

LLM development

Post-training methods

Publications in top conferences

Advanced CS degree

Education

PhD or Masters in Computer Science or related field

Job description

Scale AI, Inc. is seeking a Machine Learning Research Scientist for Enterprise GenAI to advance RL-based agent systems and post-training techniques in real-world datasets.

You will train state-of-the-art models for enterprise customers and contribute novel algorithms to our training stack, delivering high-impact agents with robust rewards and tooling. The role emphasizes cutting-edge research, publication in top venues, and collaboration with a global team in a dynamic GenAI environment.