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$31K

$63.4K

$86.9K

How much do reinforcement learning jobs pay per year?

As of Jul 20, 2026, the average yearly pay for reinforcement learning in Boston, MA is $63,388.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,900.00 and $73,900.00 per year, depending on experience, location, and employer.

Will MLE be replaced by AI?

In reinforcement learning, machine learning engineers (MLEs) design, implement, and optimize algorithms that enable AI systems to learn from interactions. While AI continues to advance, MLEs play a crucial role in developing and fine-tuning models, and their skills remain essential for deploying effective reinforcement learning solutions. The role is evolving with increased automation, but MLEs are unlikely to be fully replaced in the near term.

What are the common responsibilities of a Reinforcement Learning professional on a daily basis?

A typical day for a Reinforcement Learning professional involves designing and implementing learning algorithms, running experiments, analyzing data, and iterating on models to improve performance. You might collaborate closely with data scientists, software engineers, and product managers to integrate your solutions into broader systems or products. Regular activities also include reading recent research literature and participating in team meetings to discuss progress and obstacles. This dynamic role often balances deep technical work with teamwork to drive innovative applications in areas such as robotics, recommendation systems, or autonomous systems.

What are the key skills and qualifications needed to thrive in the Reinforcement Learning position, and why are they important?

To thrive in a Reinforcement Learning role, you need a solid background in mathematics, statistics, machine learning, and programming (commonly with Python), typically supported by a relevant degree such as in computer science or engineering. Experience with frameworks like TensorFlow, PyTorch, OpenAI Gym, and familiarity with large-scale computing systems are highly valued. Strong problem-solving abilities, curiosity, and effective collaboration and communication skills help you excel in multidisciplinary research and project teams. These capabilities are crucial for designing, implementing, and refining complex algorithms that learn from interaction to solve real-world problems.

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 or higher, especially in top tech companies or specialized research roles. Compensation often includes base salary, bonuses, and stock options, reflecting expertise in AI, deep learning, and programming languages like Python or C++.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior reinforcement learning engineer or research scientist, often requiring advanced skills in machine learning, deep learning, and programming. These roles usually involve leading projects, developing innovative algorithms, and may require extensive experience and specialized certifications. Compensation at this level reflects the expertise and impact expected in cutting-edge AI development environments.

What is a Reinforcement Learning job?

A Reinforcement Learning (RL) job involves designing, developing, and optimizing algorithms that enable machines to learn from interactions with their environment. RL professionals work on applications in robotics, finance, gaming, and autonomous systems, leveraging techniques like deep reinforcement learning and policy optimization. Responsibilities often include researching new models, implementing RL algorithms, and improving AI performance. Strong programming skills, knowledge of machine learning frameworks, and an understanding of mathematical concepts like probability and optimization are essential.

Which 3 jobs will survive AI?

Reinforcement Learning specialists, data scientists, and AI ethics professionals are likely to remain in demand as AI advances, due to their specialized skills in developing, managing, and overseeing AI systems. These roles require advanced knowledge of algorithms, programming, and ethical considerations, making them less susceptible to automation. Continuous learning and expertise in AI tools and frameworks are essential for long-term job security in these fields.
What are the most commonly searched types of Reinforcement Learning jobs in Boston, MA? The most popular types of Reinforcement Learning jobs in Boston, MA are:
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Reinforcement Learning jobs near you
Infographic showing various Reinforcement Learning job openings in Boston, MA as of July 2026, with employment types broken down into 2% Internship, 58% Full Time, 35% Part Time, and 5% Contract. Highlights an 100% In-person job distribution, with an average salary of $63,388 per year, or $30.5 per hour.

Reinforcement Learning Engineer - Locomanipulation

Humanoid

Boston, MA • On-site

$200K - $350K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 29 days ago

Job description

Here at Humanoid, we believe in a future where robots amplify human potential. That's why we've set out on a mission to build the world's most capable, commercially-scalable, and safe humanoid robots. We're bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we're growing the team to take it even further.
About the Role
We are looking for a Senior or Staff Reinforcement Learning Engineer to develop learning-based control policies for humanoid robots.
You will design and train reinforcement learning policies that enable dynamic locomotion and loco-manipulation behaviors on real robots. Your work will focus on building scalable training pipelines, designing reward functions and environments, and improving sim-to-real transfer for reliable deployment on hardware.
You will work closely with control and robotics engineers to integrate learned policies into the robot control stack, ensuring stable and robust behavior in real-world conditions.
Development will involve continuous iteration between large-scale simulation and hardware experiments.
The problems you will work on include dynamic locomotion, balance recovery, contact-rich manipulation, and multi-behavior policy learning.
What You'll Do
  • Design and train reinforcement learning policies for humanoid robot control.
  • Build scalable simulation and training pipelines (e.g., Isaac Lab, MuJoCo).
  • Design reward functions, observation spaces, and curricula for complex behaviors.
  • Improve robustness and sim-to-real transfer of learned policies.
  • Deploy and evaluate policies on real robotic systems.
  • Integrate policies into the control stack.

What We're Looking For
  • MS or PhD in Robotics, Machine Learning, Computer Science, or related field.
  • Strong experience with reinforcement learning (e.g., PPO, SAC, offline RL).
  • Experience applying RL to robotics or physical systems.
  • Experience deploying learned policies on real robotic systems.
  • Experience with physics-based simulation environments (e.g., Isaac Lab, MuJoCo).
  • Strong programming skills in Python and/or C++.
Nice to have
  • Experience with RL for locomotion or legged robots.
  • Experience with sim-to-real transfer.
  • Familiarity with robot dynamics, control, or whole-body control.

What We Offer
  • Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources.
  • Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays.
  • 401(k) retirement plan with employer match.
  • Equity included-we believe builders should share in what they build.
  • Free daily catered lunch, snacks, and drinks in‑office.
  • Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.
  • Freedom to influence the product and own key initiatives.

For this role in Massachusetts, the expected base salary range is $200K-$350K USD per year; your placement in that range depends on how your experience maps to our internal leveling.

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