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Internship Deep Reinforcement Learning Jobs in Illinois

Lightspeed

AI & Machine Learning Engineer

Northbrook, IL · On-site

... Develop reinforcement learning and imitation learning systems for robot task planning • Build ... Required : • 4+ years hands-on ML engineering building and deploying production models • Deep ...

Lightspeed

AI & Machine Learning Engineer

Northbrook, IL · On-site

$100 - $130/hr

Develop reinforcement learning and imitation learning systems for robot task planning * Build ... Develop deep learning pipelines for object detection, segmentation, and pose estimation * Build ...

Pocket FM

Senior Research Scientist

Mundelein, IL · On-site

$100K - $128K/yr

Train and fine-tune models using SFT, RLHF, DPO, LoRA, and reinforcement learning and build the ... Strong Python skills and a solid foundation in modern deep learning and generative AI architectures ...

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KenkoTech Futures

AI Scientist

Mundelein, IL · On-site

Experience developing, training or evaluating large deep learning models * Strong programming ... Reinforcement Learning * Large-Scale Distributed Training * Single-Cell Foundation Models Why Join

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Internship Deep Reinforcement Learning information

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 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 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.

What are the most commonly searched types of Deep Reinforcement Learning jobs in Illinois?

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Cities in Illinois with the most Internship Deep Reinforcement Learning job openings:

Internship Deep Reinforcement Learning jobs near you

Research Scientist/Research Engineer, Reinforcement Learning

Jump Trading

Chicago, IL • On-site

$200K - $350K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago

Job description

Jump Trading Group is committed to world-class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting-edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivizing collaboration and mutual respect. At Jump, research outcomes drive more than superior risk-adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.
Our team is a group of quantitative researchers, engineers, and ML experts leading reinforcement learning research and trading at Jump. Our mission is to combine emerging techniques and original research to learn optimal decision-making policies from financial market data and monetize them globally. We are building the future of ML-powered trading through breakthrough reinforcement learning, and we're looking for an exceptional Research Scientist/Research Engineer to join our team.
What You'll Do
As a Research Scientist/Research Engineer working on RL, you'll be at the forefront of applying reinforcement learning to markets. You'll conduct original research and own the systems that turn it into production trading: designing and evaluating policy architectures, reward formulations, and objective horizons with rigorous out-of-sample benchmarking; partnering with trading and research teams to source, integrate, and validate their alpha signals within the RL framework; ensuring simulation fidelity against live trading by modeling market microstructure, fill dynamics, liquidity, and latency; building efficient tooling to store, process, and analyze very large volumes of market and signal data; and communicating findings to technical and trading audiences. This isn't incremental optimization; we're pushing the boundaries of what reinforcement learning can do at scale, where your improvements directly impact live trading.
Other duties as assigned or needed.
Skills You'll Need
  • 5+ years of experience developing reinforcement learning and/or deep learning systems with measurable impact in industry and/or academia
  • Depth in reinforcement learning, including experience designing reward formulations, policy architectures, and evaluation, and taking RL methods from research into production
  • Proficiency in Python and/or C++
  • Familiarity with ML libraries/frameworks such as PyTorch (preferred), TensorFlow, and/or JAX
  • Strong foundation in mathematics and statistics
  • PhD or Master's degree in Computer Science, Machine Learning, Robotics (or a related subject)
  • Strong publication record at ICML, ICLR, AAAI, NeurIPS, CVPR, or equivalent
  • Ability to thrive in a collaborative, team-oriented environment
  • Creative thinkers who are driven, self-motivated, and eager to solve challenging problems
  • Reliable and predictable availability
  • Excellent written and verbal communication skills in English

Benefits
  • Discretionary bonus eligibility
  • Medical, dental, and vision insurance
  • HSA, FSA, and Dependent Care options
  • Employer Paid Group Term Life and AD&D Insurance
  • Voluntary Life & AD&D insurance
  • Paid vacation plus paid holidays
  • Retirement plan with employer match
  • Paid parental leave
  • Wellness Programs

Annual Base Salary Range
$200,000-$350,000 USD

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