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Reinforcement Learning Engineer Salary Jobs (NOW HIRING)

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

The Senior Reinforcement Learning Engineer will leverage their expertise in reinforcement learning to solve locomotion and manipulation challenges, mentor junior engineers, and implement advanced ...

Apptronik

Reinforcement Learning Engineer

Austin, TX · On-site

As a Reinforcement Learning Engineer, you will be a core contributor to the intelligence and physical capabilities of our humanoid platforms. This role is dedicated to architecting sophisticated ...

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

The Senior Reinforcement Learning Engineer will focus on achieving state-of-the-art performance on humanoid robots, leveraging expertise in reinforcement learning to solve locomotion and manipulation ...

Apptronik

Reinforcement Learning Engineer

Austin, TX · On-site

As a Reinforcement Learning Engineer, you will be a core contributor to the intelligence and physical capabilities of our humanoid platforms. This role is dedicated to architecting sophisticated ...

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

JOB SUMMARY The Senior Reinforcement Learning Engineer is a key, hands-on role focused on achieving state-of-the-art performance on our humanoid robots. This engineer will leverage their deep ...

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

JOB SUMMARY The Senior Reinforcement Learning Engineer is a key, hands-on role focused on achieving state-of-the-art performance on our humanoid robots. This engineer will leverage their deep ...

Trunk Tools

Applied Reinforcement Learning Engineer

Applied Reinforcement Learning Engineer Location: Palo Alto, CA or Seattle, WA (Hybrid/Remote ... Salary: $150K - $300K Annually Centific is an equal-opportunity employer. All qualified applicants ...

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Reinforcement Learning Engineer Salary information

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$38K

$115.9K

$191.5K

How much do reinforcement learning engineer salary jobs pay per year?

As of Sep 1, 2026, the average yearly pay for reinforcement learning engineer salary in the United States is $115,864.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,000.00 and $151,500.00 per year, depending on experience, location, and employer.

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

Reinforcement Learning Engineer SalaryMachine Learning Engineer Salary
Average salary varies based on experience, location, and industry, typically ranging from $100,000 to $150,000 annually.Average salary also varies widely, generally between $90,000 and $140,000 annually, depending on similar factors.

Both roles require strong programming skills, knowledge of machine learning frameworks, and experience with data analysis. Reinforcement Learning Engineers focus specifically on developing algorithms for decision-making tasks, while Machine Learning Engineers work on broader AI models. Salaries are comparable, with Reinforcement Learning Engineers often earning slightly more in specialized industries.

What is the salary of reinforcement learning engineer?

The salary of a reinforcement learning engineer typically ranges from $100,000 to $160,000 annually, depending on experience, location, and industry. Senior roles or those in high-demand areas may offer higher compensation, often including benefits such as stock options and bonuses.
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Reinforcement Learning Engineer Salary jobs near you
Infographic showing various Reinforcement Learning Engineer Salary job openings in the United States as of August 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $115,864 per year, or $55.7 per hour.

Machine Learning Engineer, Reinforcement Learning

Skild AI

Pittsburgh, PA • On-site

$100K - $300K/yr

Full-time

Re-posted 12 days ago

Job description

Company Overview
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
Position Overview
We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.
Responsibilities
  • Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
  • Design and conduct experiments to train RL models and conduct real-world tests.
  • Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.
  • Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.
  • Analyze and interpret experimental results, iterating on model design to achieve desired performance.
  • Stay up-to-date with the latest research and advancements in reinforcement learning.
Preferred Qualifications
  • BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
  • Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
  • Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
  • Strong background in algorithms, data structures, and software engineering principles.
  • Experience with physics simulation engines and tools for training RL.
  • Deep understanding of state-of-the-art machine learning techniques and models.
  • Extensive industry experience with reinforcement learning and robotic systems.

Base Salary Range
$100,000-$300,000 USD

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