Research Intern - Applied Reinforcement Learning

Role Summary

Centific AI Research seeks a PhD Research Intern to design and evaluate reinforcement learning (RL) systems for agentic AI workflows. You will develop RL environments, reward models, and post-training pipelines for LLM-based agents, translating research into practical enterprise solutions.

PhD Research Intern - Applied Reinforcement Learning

Scope of Work

- End-to-end RL pipelines for agentic systems (simulation → training → evaluation)

- Alignment of LLM-based agents using RLHF, DPO, PPO, and emerging methods

- Design of reward functions, verifiers, and evaluation frameworks

- Simulation environments (digital twins) for enterprise workflows

- Scalable training and inference for RL-based systems

Example Projects

- Build a custom RL environment simulating a real-world enterprise workflow and train an agent using PPO or GRPO

- Develop a reward modeling pipeline from human feedback and evaluate alignment improvements

- Create an evaluation harness measuring reasoning, task success, and policy safety

- Prototype an agentic system with tool use and multi-step reasoning, integrated with RL training

- Document experiments, ablations, and findings for research and productionization

Minimum Qualifications

- PhD candidate in CS, ML, or related field with research in reinforcement learning or agentic AI

- Strong Python and PyTorch skills with GPU-based training experience

- Solid understanding of RL fundamentals (MDPs, policy gradients, value methods)

- Experience with LLMs and post-training techniques (RLHF, DPO, PPO, etc.)

- Strong experimentation practices (ablation, reproducibility, clear reporting)

Preferred Qualifications

- Experience with RL environments (Gymnasium, RLlib, Stable Baselines)

- Research in offline RL, model-based RL, or hierarchical RL

- Publications at top ML conferences (NeurIPS, ICML, ICLR, ACL)

- Experience with simulation, synthetic data, or multi-agent systems

- Distributed training and large-scale experimentation

Tech Stack

- PyTorch, CUDA; RL libraries (Gymnasium, RLlib, Stable Baselines)

- LLM frameworks and post-training tools (TRL, custom RLHF pipelines)

- Experiment tracking (Weights & Biases)

- APIs/services (FastAPI, gRPC); optimization (ONNX, TensorRT)

Logistics

Location: Palo Alto, CA (Preferred), Redmond, WA (Preferred) or Remote

Duration: 3–6 months

Rate: $40-$45 Hourly

Learn more about us at centific.com.

Centific is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, citizenship status, age, mental or physical disability, medical condition, sex (including pregnancy), gender identity or expression, sexual orientation, marital status, familial status, veteran status, or any other characteristic protected by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.