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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 ...

Statheros

Develop and train reinforcement learning models for real-world applications, focusing on efficiency ... Remote work location. * Competitive salary. * Flexible work schedule. * Opportunities for ...

Truveta

ML PhD Intern - LLMs & Generative AI

Seattle, WA · Remote

... remote Who We Need We are seeking a highly motivated and talented Machine Learning PhD Intern to ... Familiarity with parameter-efficient tuning techniques, Reinforcement Learning from Human Feedback ...

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

As of Jun 29, 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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Remote Reinforcement Learning Intern jobs near you
Infographic showing various Remote Reinforcement Learning Intern job openings in the United States as of June 2026, with employment types broken down into 25% Full Time, 25% Temporary, and 50% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $35,436 per year, or $17 per hour.

Senior ML Scientist (Pricing Reinforcement Learning)

Futran Tech Solutions Pvt. Ltd.

Remote

Full-time

Posted 16 days ago

Job description

Senior ML Scientist (Pricing Reinforcement Learning)
Plano TX- Remote
Key Responsibilities
Algorithm Development Conceptualize design and implement state-of-the-art ML models for dynamic pricing and personalized recommendations
Reinforcement Learning Expertise Develop and apply RL techniques including Contextual Bandits Qlearning SARSA and concepts like Thompson Sampling and Bayesian Optimization to solve pricing and optimization challenges
AI Agents for Pricing Build AIdriven pricing agents that incorporate consumer behaviour demand elasticity and competitive insights to optimize revenue and conversion
Rapid ML Prototyping Experience in quickly building testing and iterating on ML prototypes to validate ideas and refine algorithms
Feature Engineering Engineer largescale consumer behavioural feature stores to support ML models ensuring scalability and performance
CrossFunctional Collaboration Work closely with Marketing Product and Sales teams to ensure solutions align with strategic objectives and deliver measurable impact
Controlled Experiments Design analyze and troubleshoot AB and multivariate tests to validate the effectiveness of your models
Qualifications
8 years in machine learning 5 years in reinforcement learning recommendation systems pricing algorithms pattern recognition or artificial intelligence
Expertise in classical ML techniques eg Classification Clustering Regression using algorithms like XGBoost Random Forest SVM and KMeans with handson experience in RL methods such as Contextual Bandits Qlearning SARSA and Bayesian approaches for pricing optimization
Proficiency in handling tabular data including sparsity cardinality analysis standardization and encoding
Proficient in Python and SQL including Window Functions Group By Joins and Partitioning
Experience with ML frameworks and libraries such as scikitlearn TensorFlow and PyTorch
Knowledge of controlled experimentation techniques including causal AB testing and multivariate testing
Required Skills:
5+ Yrs Expereince in Pricing Reinforcement Learning
8+ Yrs Experience in Machine Learning
Expert in Python & Tabular Data
SQL
Knowledge of AB Testing

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