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Reinforcement Learning Intern Jobs in Berkeley, CA

Workato

Intern, AI Engineering

San Francisco, CA · On-site

We are now filling intern positions for Winter 2026 and Spring 2027. Research Areas * LLM Agent ... Develop novel methods for parameter-efficient adaptation, alignment, and reinforcement learning for ...

Workato

Intern, AI Engineering

San Francisco, CA

$19.75 - $25.50/hr

We are now filling intern positions for Winter 2026 and Spring 2027. Research Areas * LLM Agent ... Develop novel methods for parameter-efficient adaptation, alignment, and reinforcement learning for ...

Workato

Intern, AI Engineering

San Francisco, CA · On-site

$19.75 - $25.50/hr

We are now filling intern positions for Winter 2026 and Spring 2027. Research Areas * LLM Agent ... Develop novel methods for parameter-efficient adaptation, alignment, and reinforcement learning for ...

pony.ai

Research Intern - Deep Learning

Fremont, CA · On-site

$7.0K - $10K/mo

Frame the open-ended real-world problems into well-defined ML problems; develop and apply cutting-edge ML approaches (deep learning, reinforcement learning, imitation learning, etc) to these problems ...

pony.ai

Research Intern - Deep Learning

Fremont, CA

$7.0K - $10K/mo

Frame the open-ended real-world problems into well-defined ML problems; develop and apply cutting-edge ML approaches (deep learning, reinforcement learning, imitation learning, etc) to these problems ...

pony.ai

Research Intern - Deep Learning

Fremont, CA · On-site

$7.0K - $10K/mo

Frame the open-ended real-world problems into well-defined ML problems; develop and apply cutting-edge ML approaches (deep learning, reinforcement learning, imitation learning, etc) to these problems ...

Faire

Data Science Intern

San Francisco, CA

$75/hr

Apply exploration-exploitation strategies - including contextual bandits and reinforcement learning - to optimize recommendations under uncertainty * Advance recommendation quality through ...

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How much do reinforcement learning intern jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for reinforcement learning intern in Berkeley, CA is $20.86, according to ZipRecruiter salary data. Most workers in this role earn between $17.64 and $23.56 per hour, depending on experience, location, and employer.

What kinds of projects or tasks can I expect to work on as a reinforcement learning intern?

As a Reinforcement Learning Intern, you will typically work on tasks such as designing, implementing, and testing reinforcement learning algorithms, analyzing experimental results, and assisting with data preprocessing or environment development. You may also collaborate with senior researchers and engineers, participate in code reviews, and contribute to technical discussions or team meetings. In many organizations, interns are given the chance to work on real-world problems—ranging from optimizing robotic control systems to enhancing recommendation engines. This hands-on experience not only builds your technical expertise but also helps you develop valuable teamwork and communication skills, preparing you for a future career in AI or machine learning.

What is a reinforcement learning intern?

A Reinforcement Learning (RL) Intern is responsible for researching, developing, and testing RL algorithms to solve complex problems. They typically work on tasks such as implementing reinforcement learning models, optimizing reward functions, and running experiments in simulated environments. Interns collaborate with researchers and engineers to refine models and improve the efficiency of RL systems. They usually have experience in machine learning, deep learning, and programming languages like Python. The role provides hands-on experience in applying RL techniques to real-world applications.

What are the key skills and qualifications needed to thrive as a reinforcement learning intern?

To thrive as a Reinforcement Learning Intern, you need strong knowledge of machine learning fundamentals, programming proficiency (usually in Python), and a background in mathematics or computer science, often demonstrated through academic coursework or relevant projects. Familiarity with popular machine learning libraries such as TensorFlow, PyTorch, and RL-specific frameworks like OpenAI Gym is typically expected. Effective problem-solving skills, attention to detail, and the ability to communicate technical findings clearly are valuable soft skills in this position. These capabilities enable interns to contribute meaningfully to research and development efforts, bridging theory and practical application in real-world reinforcement learning projects.

What job categories do people searching Reinforcement Learning Intern jobs in Berkeley, CA look for? The top searched job categories for Reinforcement Learning Intern jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Reinforcement Learning Intern jobs? Cities near Berkeley, CA with the most Reinforcement Learning Intern job openings:
Reinforcement Learning Intern jobs near you

Machine Learning Engineer - ML Agents, Planning

Jobtailor

Foster City, CA • On-site

$180 - $250/hr

Other

Posted 6 days ago

Job description

  • You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for human-like agents.
  • You will work on novel techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort and realism.
  • You will contribute to our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
  • You will develop metrics and tools to analyze errors and understand improvements of our systems
  • You will collaborate with engineers on Perception, Planning, Simulation, and Validation to solve the overall Autonomous Driving problem.
Requirements
  • PhD degree in computer science or related field or master's degree and 5+ years of professional experience in a relevant field.
  • Experience in Planning and / or Prediction using Reinforcement Learning techniques
  • Experience with training and deploying transformer-based model architectures
  • Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
  • Fluency in Python with a basic understanding of C++
Core Competencies

Expertise in developing deep learning models for autonomous driving, with a focus on imitation learning and reinforcement learning. Proficient in creating and analyzing machine learning pipelines, metrics, and tools to enhance system performance and safety.

Highest-signal resume keywords
  • PhD In Computer Science
  • Reinforcement Learning Techniques
  • Transformer-Based Model Architectures
  • Production Machine Learning Pipelines
  • Fluency In Python
ATS Optimization Keywords Hard Skills
  • Deep Learning Models
  • Imitation Learning
  • Reinforcement Learning
  • Planning
  • Prediction
  • Metrics Development
  • Error Analysis
  • Dataset Creation
  • Training Frameworks
  • Model Deployment
Industry Keywords
  • Autonomous Driving
  • Safety
  • Comfort
  • Realism
  • Collaboration
Tools & Technologies
  • Machine Learning Infrastructure
  • Python
  • C++
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