RL Researcher, Product Systems

Autohand AI Ltd.; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Publications

Job summary

Autohand AI Ltd. in San Francisco is seeking a Reinforcement Learning Researcher with a strong product mindset to join our research team.

You'll develop RL systems that enable autonomous programming agents to learn and improve from real-world feedback. The role emphasizes designing reward functions, training pipelines, and evaluation frameworks that push the boundaries of what autonomous systems can achieve.

Qualifications

• PhD or equivalent in RL/ML is required.
• Strong track record in reinforcement learning research.
• Experience shipping ML systems to production.
• Product-oriented mindset with ability to prioritize impactful research.

Responsibilities

• Design and implement RL algorithms for autonomous code generation and modification.
• Develop reward models and training pipelines that align with product goals.
• Build evaluation frameworks to measure agent performance and safety.
• Collaborate with product teams to understand user needs and translate them into research directions.
• Ship research to production and iterate based on real-world feedback.
• Contribute to technical publications and open-source releases.

Skills

Product-oriented mindset

Strong RL research track record

Excellent communication

Cross-functional collaboration

Education

PhD or equivalent in RL/ML

Tools

Python

PyTorch

JAX

Job description

We're looking for a Reinforcement Learning Researcher with a strong product mindset to join our research team. You'll develop RL systems that enable autonomous programming agents to learn and improve from real-world feedback.

This role is ideal for someone who wants their research to directly impact products. You'll design reward functions, training pipelines, and evaluation frameworks that push the boundaries of what autonomous systems can achieve.

What you'll do

• Design and implement RL algorithms for autonomous code generation and modification
• Develop reward models and training pipelines that align with product goals
• Build evaluation frameworks to measure agent performance and safety
• Collaborate with product teams to understand user needs and translate them into research directions
• Ship research to production and iterate based on real-world feedback
• Contribute to technical publications and open-source releases

What we're looking for

• PhD or equivalent experience in RL, ML, or related fields
• Strong track record in reinforcement learning research
• Experience shipping ML systems to production
• Product-oriented mindset with ability to prioritize impactful research
• Proficiency in Python and deep learning frameworks (PyTorch, JAX)
• Excellent communication skills and ability to work cross-functionally

Nice to have

• Publications in top ML venues (NeurIPS, ICML, ICLR, CoRL)
• Experience with RLHF or preference learning
• Background in LLMs or code generation
• Experience with distributed training at scale
• Previous startup or product-focused research experience

Preferred Candidates

You must be a citizen or have authorised work permit in one of the locations where we hire: Australia, New Zealand, Brazil, Singapore, or the United States.