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Internship Deep Reinforcement Learning Jobs in Rochester, NY

Varsity Tutors

BCABA Tutor

Rochester, NY · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of BCABA examination content covering basic behavior-analytic skills, philosophical ...

Kharma Care LLC

Lead Teacher

Rochester, NY · On-site

$18.50 - $25/hr

... learning, independence, and social-emotional development. Key Responsibilities: Classroom ... Supervise and mentor Assistant Teachers, Classroom Aides, and interns. * Work in partnership with ...

Kharma Care LLC

Lead Teacher

Rochester, NY · On-site

$18.50 - $25/hr

... learning, independence, and social-emotional development. Key Responsibilities: Classroom ... Supervise and mentor Assistant Teachers, Classroom Aides, and interns. * Work in partnership with ...

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How much do internship deep reinforcement learning jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for internship deep reinforcement learning in Rochester, NY is $16.81, according to ZipRecruiter salary data. Most workers in this role earn between $14.23 and $18.99 per hour, depending on experience, location, and employer.

What types of projects or tasks can I expect to work on during a deep reinforcement learning internship?

As a Deep Reinforcement Learning (DRL) intern, you'll typically work on projects involving the development, implementation, and evaluation of reinforcement learning algorithms. This might include tasks like training agents in simulated environments, tuning hyperparameters, analyzing performance metrics, and collaborating with team members to integrate DRL solutions into larger systems. You'll also likely spend time reading recent research papers, experimenting with frameworks such as TensorFlow or PyTorch, and presenting your findings to the research team. Collaboration with mentors and other interns is common, and you'll gain hands-on experience that prepares you for more advanced roles in AI research or engineering.

What is an internship in deep reinforcement learning?

An internship in Deep Reinforcement Learning (DRL) is a temporary, hands-on position where interns learn and apply state-of-the-art machine learning algorithms that enable computers to learn decision-making tasks through trial and error. Interns typically work on projects involving neural networks, reward systems, and environments like games or simulations. These internships provide valuable experience with frameworks such as TensorFlow or PyTorch, and exposure to current research in artificial intelligence. The experience helps students or recent graduates build technical skills and prepare for careers in AI research or industry.

What are the key skills and qualifications needed to thrive as an intern in deep reinforcement learning?

To thrive as an Intern in Deep Reinforcement Learning, you need a solid background in mathematics (especially linear algebra, probability, and calculus), programming (Python), and foundational knowledge in machine learning principles, usually supported by ongoing or completed coursework in computer science or related fields. Familiarity with frameworks and tools such as TensorFlow, PyTorch, OpenAI Gym, and experience using version control systems like Git are typically required. Analytical thinking, curiosity, and effective communication are essential soft skills for collaborating on research problems and sharing complex findings. These skills and qualities are crucial for contributing to innovative projects and successfully navigating the challenges of cutting-edge AI research.

What is the difference between Internship Deep Reinforcement Learning vs Data Science Intern?

AspectInternship Deep Reinforcement LearningData Science Intern
Required SkillsMachine learning, programming (Python), reinforcement learning conceptsStatistics, data analysis, programming (Python/R), data visualization
Work EnvironmentResearch labs, AI companies, tech startupsBusiness analytics, tech firms, consulting agencies
Industry UsageAI research, robotics, autonomous systemsBusiness intelligence, marketing, finance

Internship Deep Reinforcement Learning focuses on developing algorithms that enable systems to learn through trial and error, often in AI research or robotics. Data Science Internships involve analyzing data to extract insights and support decision-making. While both roles require programming skills, reinforcement learning emphasizes AI-specific techniques, whereas data science centers on statistical analysis and data visualization.

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Internship Deep Reinforcement Learning jobs near you
Infographic showing various Internship Deep Reinforcement Learning job openings in Rochester, NY as of June 2026, with employment types broken down into 9% As Needed, 52% Full Time, 15% Part Time, 9% Temporary, and 15% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $34,963 per year, or $16.8 per hour.

Global Quantitative Strategies | Machine Learning Researcher

Citadel LLC

Rochester, NY • On-site

$300 - $350/hr

Other

Medical, Life, Retirement

Posted 11 days ago

Job description

About GQS

GQS is the quantitative investment business of Citadel. Founded in 2012, GQS has grown rapidly to become one of Citadel’s core investment strategies and one of the top quantitative investment teams in the world. Collaborative teams of researchers, engineers, and traders build robust systems that operate at scale and apply advanced quantitative and machine learning techniques to identify investment opportunities.

Role Overview

Machine Learning Researchers at GQS develop and deploy models across a variety of asset classes. Their work spans deep learning, sequence and time-series modeling, natural language processing, large language models, pre-training, reinforcement learning, and methods for improving robustness in complex financial regimes.

Location

New York, Singapore

Required Skills and Qualifications
  • Advanced degree in Computer Science, Machine Learning, Mathematics, Statistics, Engineering, Physics, or a related quantitative field
  • Proven ability to conduct innovative and impactful research focused on solving real-world problems
  • Deep expertise in machine learning and deep learning, such as sequence modeling, large language models, or reinforcement learning
  • Experience with modern training techniques such as pre-training, fine-tuning, reinforcement learning, or related optimization methods
  • Expertise in Python and machine learning frameworks such as PyTorch or JAX
  • Strong mathematical and statistical foundations
  • Ability to design, implement, and optimize machine learning models for performance, scalability, and robustness
  • Demonstrated interest in financial markets and a drive to apply machine learning techniques to model price formation, market behavior, and risk
Compensation and Benefits

In accordance with applicable law, the base salary range for this role is $300,000 to $350,000. In addition, the employee who fills this role will be eligible to participate in a discretionary incentive compensation program, as well as a wide array of benefit programs, such as medical and life insurance, retirement and tax-free savings plans, and access to other healthcare programs.

Personal Data Use

We collect and use personal data in accordance with our Privacy Policy. We retain data on prospective candidates and may consider suitability for alternative opportunities at Citadel. For more information, see our Privacy Policy.

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