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Remote Reinforcement Learning Intern Jobs (NOW HIRING)

Motional

Senior Machine Learning Engineer, Data Mining

$125K - $165K/yr

Reinforcement Learning for Data Discover : Build RL-based policy learning and reasoning systems for ... be fully remote. The salary range for this role is an estimate based on a wide range of ...

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 ...

Keebo

Senior Machine Learning Engineer

$125K - $165K/yr

Experience with Reinforcement Learning * Experience with Google Cloud and BigQuery Our Environment Keebo is a fully remote, global team with team members currently in the US, EU, and Canada. What we ...

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

As of Jun 9, 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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Senior Machine Learning Engineer - VLM/LLM Evaluation

Senior Machine Learning Engineer - VLM/LLM Evaluation

Waymo

Kirkland, WA • On-site, Remote

$204K - $259K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago

Job description

Senior Machine Learning Engineer – VLM/LLM Evaluation

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.

This role follows a hybrid work schedule and you will report to a Senior Staff Software Engineer.

You will:

  • Work with a creative team of people who help to build the state-of-the-art Foundation Models that are used throughout Waymo's systems, both onboard autonomous vehicles and offboard in simulation
  • Drive the development or significantly contribute to end-to-end evaluation systems and benchmarks for Waymo Foundation models, encompassing the entire life-cycle from pre-training and supervised fine-tuning (SFT) to reinforcement learning (RL), for evaluating the quality, safety, and realism of embodied AI agents
  • Partner with cross-functional teams within the organization to land innovative tech in production
  • Implement and extend large scale data and evaluation pipelines.

You have:

  • Bachelor or Master's degree in Computer Science, similar technical field of study, or equivalent practical experience
  • Experience in ML engineering and applied Deep Learning
  • Experience with large scale distributed system
  • Proficient programming skills (eg: Python, C/C++)

We prefer:

  • ML infra experience: training, evaluating and deploying ML models at scale
  • Deep learning experience, especially with generative models, e.g., LLMs/VLMs, and/or reinforcement learning
  • Proficiency and in-depth knowledge of the inner workings of an ML framework (e.g. Pytorch, JAX, Tensorflow)

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

  • Health, dental, vision, life, disability insurance
  • Retirement Benefits: 401(k) with company match
  • Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
  • Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
  • Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
  • Baby Bonding Leave: 18 weeks
  • Holidays: 13 paid days per year

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range $204,000—$259,000 USD

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