Remote RL AI Research Scientist: Build Scalable Agents

Pokee AI; United States; Remote; USD 150,000 - 230,000; Full time

Job summary

Pokee AI is seeking an RL Research Scientist to join a team building the reinforcement learning foundation of an AI agent platform. The role focuses on long-horizon planning, reward shaping, and context selection to enable reliable operation at scale.

Remote role with a preference for candidates based in the US or Singapore. You will design and implement novel RL algorithms, develop reward models, and run large-scale experiments, translating insights into production-ready components while

Qualifications

• PhD or equivalent research experience in RL, ML, or a closely related field.
• Strong publication record at top venues (NeurIPS, ICML, ICLR, AAAI).
• Deep expertise in RL fundamentals (policy gradients, value methods, model-based RL, multi-agent RL, RLHF/RLAIF).
• Proficiency in Python and at least one DL framework; PyTorch preferred.
• Proven ability to translate research from prototype to production.

Responsibilities

• Design and implement novel RL algorithms for training agents on complex, multi-step enterprise workflows.
• Develop reward modeling, context selection, and policy optimization techniques for long horizons.
• Run large-scale experiments, analyze results, and translate research into production-ready components.
• Collaborate with infrastructure engineers to scale research prototypes on cloud and on-device hardware.
• Track advances in RL, LLM fine-tuning, and agent architectures; propose new directions.
• Contribute to IP through publications, patents, and open-source work.

Skills

Reinforcement Learning

Machine Learning

Python

PyTorch

Research to Production

Education

PhD or equivalent RL/ML research

Job description

Pokee AI is seeking an RL Research Scientist to join a team building the reinforcement learning foundation of an AI agent platform. The role focuses on long-horizon planning, reward shaping, and context selection to enable reliable operation at scale.

Remote role with a preference for candidates based in the US or Singapore. You will design and implement novel RL algorithms, develop reward models, and run large-scale experiments, translating insights into production-ready components while