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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 is a key, hands-on role focused on achieving state-of-the-art performance on our humanoid robots. This engineer will leverage their deep expertise in RL to ...

Centific

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 ...

Skild AI

Machine Learning Engineer

San Mateo, CA · On-site

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 ...

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

As of Jun 30, 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 engineers make $500,000?

Senior reinforcement learning engineers with extensive experience, advanced skills in machine learning frameworks, and a strong track record in deploying AI systems can earn salaries around $500,000, especially in high-cost-of-living areas or within leading tech companies. Such roles often require expertise in deep learning, programming in Python or C++, and knowledge of cloud platforms. Compensation may include base salary, bonuses, and stock options.

Can you make 300k a year as an engineer?

Reinforcement Learning Engineers with extensive experience, advanced skills in machine learning frameworks, and a strong track record can potentially earn salaries around or above $300,000 annually, especially in high-cost living areas or within leading tech companies. Compensation often depends on factors such as education, certifications, location, and the complexity of projects handled.

Who earns more, AI or ML engineer?

AI engineers and ML engineers typically have similar salary ranges, with salaries often depending on experience, skills, and industry. Generally, AI engineers may earn slightly more due to the broader scope of their work, which includes developing intelligent systems and deploying advanced algorithms. Both roles require expertise in programming, data analysis, and machine learning tools.

Can you make $500,000 as an electrical engineer?

Reinforcement Learning Engineers, a specialized role in AI and machine learning, can potentially earn $500,000 or more annually, especially with extensive experience, advanced skills in programming and neural networks, and work in high-paying industries or senior positions. However, typical salaries for electrical engineers are generally lower, with top-tier professionals in specialized fields earning higher compensation. Achieving such a high salary often requires advanced expertise, certifications, and working in competitive or executive roles.
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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 June 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $115,864 per year, or $55.7 per hour.
Senior Reinforcement Learning Engineer

Senior Reinforcement Learning Engineer

Apptronik

Austin, TX • On-site

$103K - $142K/yr

Full-time

Posted 3 days ago

Job description

Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. Our flagship humanoid robot, Apollo, is built to collaborate thoughtfully with people, starting with critical industries such as manufacturing and logistics, with future applications in healthcare, the home, and beyond.
We operate at the cutting edge of embodied AI, applying our expertise across the full robotics stack to solve some of society's most important problems. You will join a team dedicated to bringing Apollo to market at scale, tackling the complex challenges like safety, commercialization, and mass production to change the world for the better.
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 expertise in RL to solve critical locomotion and manipulation challenges and deliver breakthrough results on physical hardware. The primary focus of this role is to rapidly implement, iterate, and deploy advanced learning algorithms to push the boundaries of what our robots can do. As a senior member of the team, this individual will also be responsible for mentoring junior engineers, elevating the team's overall technical capabilities through their guidance and expertise.
ESSENTIAL DUTIES AND RESPONSIBILITIES or KEY ACCOUNTABILITIES:
  • Implement and deploy state-of-the-art RL algorithms to achieve ambitious, world-class performance on dynamic locomotion and manipulation tasks with physical hardware.
  • Drive the entire development cycle, from prototyping in simulation to robustly transferring and fine-tuning policies on the robot.
  • Optimize and scale the RL training pipeline for faster iteration, contributing to core infrastructure for high-throughput simulation and distributed training.
  • Mentor junior engineers by providing technical guidance, conducting insightful code reviews, and sharing best practices in reinforcement learning and software development.
  • Collaborate closely with the robotics and hardware teams to diagnose system-level issues and co-develop solutions that enable more complex learned behaviors.
  • Analyze and present hardware results to guide future technical directions and demonstrate progress on key company objectives.
SKILLS AND REQUIREMENTS
  • Deep, hands-on expertise (5+ years) with common RL frameworks (e.g., PyTorch, JAX) and high-fidelity physics simulators (e.g., MuJoCo, IsaacGym)
  • Mastery of Python for rapid prototyping and training, alongside strong proficiency in C++ for developing performant, deployable code.
  • Experience building or utilizing large-scale, distributed training pipelines and a strong intuition for their optimization.
  • A strong theoretical understanding of modern reinforcement learning, including deep expertise in areas like imitation learning, model-based RL, and sim-to-real transfer techniques.
  • A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches.
  • A results-oriented mindset with a passion for seeing complex algorithms work on real-world hardware.
EDUCATION and/or EXPERIENCE:
  • A PhD or MS in Computer Science, Robotics, or a related field, with 2+ years industry experience strongly preferred.
  • A proven track record of successfully deploying learning-based policies on physical robotic systems, especially legged robots or manipulators.
  • Demonstrated experience mentoring or providing technical guidance to other engineers in a team environment.
  • A strong publication record in relevant conferences or journals (e.g., CoRL, RSS, ICRA) is a significant plus.
PHYSICAL REQUIREMENTS:
  • Prolonged periods of sitting at a desk and working on a computer
  • Vision to read printed materials and a computer screen
  • Hearing and speech to communicate

*This is a direct hire. Please, no outside Agency solicitations.
Apptronik provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

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