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Remote Reinforcement Learning Intern Jobs (NOW HIRING)

poolside

Member of Engineering (Reinforcement Learning)

$99K - $136K/yr

ABOUT THE ROLE You would be working on our reinforcement learning team focused on improving ... Fully remote work & flexible hours * 37 days/year of vacation & holidays * Health insurance ...

Centific

Applied Reinforcement Learning Engineer

Palo Alto, CA or Seattle, WA (Hybrid/Remote) About the Team Centific AI Research advances foundational AI models and applications through reinforcement learning, alignment, and human-centered ...

The Pennsylvania State University

$20/hr

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Conduct research on multi-agent deep reinforcement learning, including designing novel algorithms ...

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How much do remote reinforcement learning intern jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for remote reinforcement learning intern in the United States is $17.04, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What does a Remote Reinforcement Learning Intern do?

A Remote Reinforcement Learning Intern assists with research and development projects that focus on reinforcement learning, a type of machine learning where agents learn to make decisions by trial and error. Their tasks often include implementing algorithms, running experiments, analyzing results, and contributing to academic papers or practical applications. Working remotely, they collaborate with teams using online tools and communicate progress regularly. The role is ideal for students or recent graduates who want to gain hands-on experience in artificial intelligence and machine learning.

What are some common challenges faced by remote reinforcement learning interns, and how can they be overcome?

Remote reinforcement learning interns often encounter challenges related to communication and collaboration, especially when working with distributed teams. It can also be difficult to access computational resources or receive timely feedback on experiments. To overcome these challenges, it's important to proactively schedule regular check-ins with mentors, utilize collaborative tools (such as Slack or GitHub), and ensure a reliable internet connection. Additionally, keeping detailed documentation and being transparent about progress can help facilitate smoother teamwork and problem-solving.

What are the key skills and qualifications needed to thrive as a Remote Reinforcement Learning Intern, and why are they important?

To thrive as a Remote Reinforcement Learning Intern, you need a strong background in mathematics, programming (especially Python), and foundational knowledge of machine learning concepts, typically demonstrated through coursework or relevant projects. Familiarity with reinforcement learning libraries (such as TensorFlow, PyTorch, or OpenAI Gym), version control systems like Git, and possibly cloud computing platforms is highly valuable. Excellent problem-solving abilities, self-motivation, and effective remote communication skills help interns excel in independent and collaborative tasks. These skills are essential for contributing to innovative research and development projects while working efficiently in a distributed team environment.
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Research Intern - Applied Reinforcement Learning

Centific

Remote

$35 - $45/hr

Full-time

Posted 15 days ago

Job description

About Centific
Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem-comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets-to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovationâ„¢ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.
Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.
About Job
PhD Research Intern - Applied Reinforcement Learning
Centific AI Research
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.
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
What We Offer
- Competitive stipend and real-world impactful projects
- Mentorship from researchers and engineers
- Access to modern GPU infrastructure
- Opportunities to publish and present research
Centific AI Research is an Equal Opportunity Employer. We celebrate diversity and are committed to an inclusive environment.
Rate: $35-$45 Hourly
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.

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