RL AI Research Scientist
Pokee AI · United States
- Hybrid
- Full-time
- $150,000 / year
- United States
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Job highlights
- Design and implement novel RL algorithms for AI agents.
- Develop advanced reward modeling and policy optimization.
- Run large-scale experiments and productionize research.
- Collaborate on scalable cloud and on-device hardware.
- Contribute to IP through publications and patents.
About the role
RL AI Research Scientist
Pokee AI is seeking a talented RL AI Research Scientist to join their remote team. This full-time role focuses on designing, implementing, and scaling novel reinforcement learning algorithms for their AI agent platform. The ideal candidate will have a PhD or equivalent research experience and a strong publication record in top AI venues.
About The Role
As an RL Research Scientist, you will design, implement, and scale novel reinforcement learning algorithms that form the core of Pokee’s AI agent platform. You’ll work at the frontier of RL applied to real-world enterprise tasks—developing methods for context selection, long-horizon planning, and reward shaping that enable agents to operate reliably at scale.
What You’ll Do
- Design and implement novel RL algorithms for training AI agents on complex, multi-step enterprise workflows
- Develop and refine reward modeling, context selection, and policy optimization techniques that improve agent accuracy over extended task horizons
- Run large-scale experiments, analyze results rigorously, and translate research findings into production-ready components
- Collaborate closely with infrastructure engineers to ensure research prototypes scale efficiently on both cloud and on-device hardware
- Contribute to the company’s intellectual property through publications, patents, and open-source contributions
- Stay current with the latest advances in RL, LLM fine-tuning, and AI agent architectures, and propose new research directions
What We’re Looking For
Required
- PhD (or equivalent research experience) in Reinforcement Learning, Machine Learning, or a closely related field
- Strong publication record at top venues (NeurIPS, ICML, ICLR, AAAI, or equivalent)
- Deep expertise in RL fundamentals: policy gradient methods, value-based methods, model-based RL, multi-agent RL, or RLHF/RLAIF
- Proficiency in Python and at least one deep learning framework (PyTorch strongly preferred)
- Experience training and fine-tuning large language models is a significant plus
- Demonstrated ability to take research from prototype to production
Bonus Points
- Experience with on-device or edge inference optimization (quantization, distillation, MoE architectures)
- Familiarity with enterprise software deployment, compliance, or regulated industries
- Track record of open-source contributions in RL or LLM ecosystems
- Experience with distributed training at scale (FSDP, DeepSpeed, Megatron)
Who You Are
You want to join a small, elite team solving one of the hardest problems in AI—building agents that actually work in the real world. You’ll have direct impact on the product, access to cutting-edge research, and the opportunity to shape the future of enterprise AI from the ground up.
Key skills/competency
- Reinforcement Learning
- Machine Learning
- Deep Learning
- Python
- PyTorch
- Large Language Models (LLMs)
- AI Agents
- Algorithm Design
- Research
- Enterprise AI
Skills & topics
- Reinforcement Learning
- AI Research Scientist
- Machine Learning
- Deep Learning
- Python
- PyTorch
- LLM
- AI Agents
- Research Scientist
- Algorithm Design
- Enterprise AI
- NeurIPS
- ICML
- ICLR
- AAAI
- RLHF
- RLAIF
- Remote
- Full-time
How to get hired
- Tailor your resume: Highlight your PhD research, publication record, and specific RL expertise (e.g., policy gradient, RLHF) relevant to Pokee AI's needs.
- Showcase your projects: Include a link to your GitHub or personal website demonstrating RL algorithm implementation, LLM fine-tuning, or production-ready code.
- Emphasize collaboration: Detail experiences working with engineers to scale research prototypes and your ability to translate research into production.
- Prepare for technical interviews: Be ready to discuss fundamental RL concepts, deep learning frameworks (PyTorch), and problem-solving scenarios for complex enterprise workflows.
- Research Pokee AI: Understand their mission to build real-world AI agents and their focus on enterprise tasks to articulate your alignment during interviews.
Technical preparation
Master RL fundamentals: policy gradients, value-based methods.,Implement algorithms using Python and PyTorch.,Fine-tune Large Language Models for agent tasks.,Practice designing scalable experiments and productionizing code.
Behavioral questions
Describe a challenging research problem you solved.,How do you collaborate with engineering teams?,Discuss your experience translating research to production.,How do you stay updated with AI advancements?
Frequently asked questions
- What are the key RL areas Pokee AI is focused on for their AI Research Scientist role?
- Pokee AI is focused on applying reinforcement learning to complex enterprise tasks. This includes developing methods for context selection, long-horizon planning, and reward shaping to enable AI agents to operate reliably at scale. Expertise in policy gradient, value-based methods, model-based RL, multi-agent RL, or RLHF/RLAIF is highly valued.
- What qualifications are essential for the RL AI Research Scientist position at Pokee AI?
- A PhD or equivalent research experience in Reinforcement Learning, Machine Learning, or a related field is required. A strong publication record at top venues like NeurIPS, ICML, ICLR, or AAAI is also crucial. Proficiency in Python and a deep learning framework, preferably PyTorch, is necessary.
- Is experience with Large Language Models (LLMs) required for the RL AI Research Scientist job at Pokee AI?
- While not strictly required, experience in training and fine-tuning large language models is a significant plus for the RL AI Research Scientist role at Pokee AI. This indicates an understanding of related AI advancements that can complement reinforcement learning efforts.
- What is the expected work arrangement and location for the RL AI Research Scientist at Pokee AI?
- The RL AI Research Scientist position is a full-time, remote role. Pokee AI prefers candidates located in the US or Singapore, but remote work is available globally. The application process includes specifying a preferred location.
- How can I best showcase my research experience for the Pokee AI RL AI Research Scientist application?
- To best showcase your research experience, ensure your resume highlights your PhD work, your publication list with venue details, and any specific contributions to RL algorithms or LLM fine-tuning. Also, be prepared to discuss your research projects in detail during interviews.
- What are the 'bonus points' for the RL AI Research Scientist role at Pokee AI?
- Bonus points for the RL AI Research Scientist role include experience with on-device or edge inference optimization, familiarity with enterprise software deployment in regulated industries, a track record of open-source contributions in RL or LLM ecosystems, and experience with distributed training at scale.
- Does Pokee AI encourage publications and patents for their RL AI Research Scientists?