ZipRecruiter

Log In

2

Remote Reinforcement Learning Jobs (NOW HIRING)

next page

Showing results 1-20

All JobsRemote Reinforcement Learning Jobs

Remote Reinforcement Learning information

See salary details

$11K

$83.9K

$140K

How much do remote reinforcement learning jobs pay per year?

As of Jun 12, 2026, the average yearly pay for remote reinforcement learning in the United States is $83,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What is a Remote Reinforcement Learning job?

A Remote Reinforcement Learning job involves developing and applying reinforcement learning algorithms while working from a location outside of a traditional office environment. Professionals in this field focus on creating systems where agents learn optimal behaviors through trial and error, often using feedback from their environment. These jobs typically require expertise in machine learning, programming, and mathematics, and are commonly found in industries like robotics, gaming, and autonomous systems. Working remotely allows researchers and engineers to collaborate with global teams using digital tools and platforms.

What are the key skills and qualifications needed to thrive as a Remote Reinforcement Learning Engineer, and why are they important?

To thrive as a Remote Reinforcement Learning Engineer, you need a strong background in machine learning, statistics, and programming (especially Python), often supported by an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and RL-specific libraries like OpenAI Gym, along with experience using cloud computing platforms, is typically required. Excellent problem-solving skills, self-motivation, and effective remote communication help individuals excel in distributed teams. These skills ensure the successful design, implementation, and deployment of reinforcement learning solutions while collaborating efficiently in a remote work environment.

What is the difference between Remote Reinforcement Learning vs Remote Machine Learning Engineer?

AspectRemote Reinforcement Learning
Required CredentialsMaster's or PhD in Computer Science, AI, or related fields; knowledge of RL algorithms
Work EnvironmentResearch-focused, experimental, often involves simulation and algorithm development
Employer & Industry UsageTech companies, research labs, AI startups focusing on autonomous systems
Common Search & Comparison IntentUnderstanding specialized AI roles, research focus, and technical skills

Remote Reinforcement Learning specialists focus on developing algorithms that enable machines to learn through trial and error in simulated or real environments. In contrast, Remote Machine Learning Engineers typically work on deploying and optimizing various machine learning models across applications. While both roles require strong programming skills and knowledge of AI, reinforcement learning emphasizes decision-making processes, whereas machine learning engineering covers a broader range of models and deployment strategies.

What are common challenges faced when working remotely in a Reinforcement Learning role and how can they be addressed?

Working remotely in a Reinforcement Learning role often involves overcoming communication barriers with cross-functional teams, managing large-scale experiments without on-site resources, and staying updated with rapidly evolving research. To address these challenges, it's important to establish regular check-ins with colleagues, utilize cloud-based platforms for experiment management, and participate in virtual seminars or journal clubs. Developing strong self-motivation and time management skills is also crucial to maintain productivity in a remote environment.
More about Remote Reinforcement Learning jobs
What cities are hiring for Remote Reinforcement Learning jobs? Cities with the most Remote Reinforcement Learning job openings:
What are the most commonly searched types of Reinforcement Learning jobs? The most popular types of Reinforcement Learning jobs are:
What states have the most Remote Reinforcement Learning jobs? States with the most job openings for Remote Reinforcement Learning jobs include:
What job categories do people searching Remote Reinforcement Learning jobs look for? The top searched job categories for Remote Reinforcement Learning jobs are:
Remote Reinforcement Learning jobs near you
Senior Staff Machine Learning Engineer, Depot Automation

Senior Staff Machine Learning Engineer, Depot Automation

Waymo

Mountain View, CA • On-site, Remote

$298K - $368K/yr

Other

Posted 5 days ago

Job description

Senior Staff Machine Learning Engineer, Depot Automation

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.

This role is at the intersection of robotics and machine learning, driving the next generation of operational efficiency for Waymo's rapidly expanding autonomous fleet. You will lead efforts to generalize complex depot operations—such as exterior cleaning, sensor calibration, and maintenance checks—using advanced robotics. Key work involves leveraging foundation models, reinforcement learning, simulation, and integrating ML models in production at scale. You will interface closely with operations teams to translate real-world needs into robust, working solutions.

This role follows a hybrid work schedule and reports to a Director, Hardware and Sensors.

You will:

  • Drive the next generation of operational efficiency for Waymo's rapidly expanding autonomous fleet.
  • Lead efforts to generalize complex depot operations using advanced robotics.
  • Focus on complex depot operations, such as exterior cleaning, sensor calibration, and maintenance checks.
  • Leverage foundation models, reinforcement learning, and simulation.
  • Integrate ML models in production at scale.
  • Interface closely with operations teams to translate real-world needs into robust, working solutions.

You have:

  • At least 10 years of experience applying machine learning techniques to large-scale industrial problems.
  • Proven experience in training and evaluating large machine learning models.
  • Expertise in reinforcement learning and its applications to real-world problems.

We prefer:

  • PhD in Machine Learning, Robotics, or a related technical field.
  • Experience in robotics or embodied AI is a plus.
  • Background in collaborating with internal and external research partners on applying ML to large-scale industry scale problems.

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 $298,000—$368,000 USD

Apply