ZipRecruiter

Log In

1

Reinforcement Learning Jobs in Washington (NOW HIRING)

Sierra Nevada Corporation

Sr AI/ML Engineer

Herndon, VA · On-site

$107K - $147K/yr

Design and prototype MPC-aligned models incorporating predictive modeling, optimization, and reinforcement-learning-based control. * Develop signal processing, perception, and planning pipelines ...

New

AHU Technologies, Inc.

AI Builder

Washington, DC · On-site

$140K - $300K/yr

Experience in applied ML, AI systems, reinforcement learning, or product engineering. * Strong understanding of ML fundamentals, evaluation methods, training, and quality measurement. * Strong ...

New

next page

Showing results 1-20

All JobsReinforcement Learning JobsReinforcement Learning Jobs in Washington

Reinforcement Learning information

See Washington salary details

$32.3K

$66.1K

$90.6K

How much do reinforcement learning jobs pay per year?

As of Jul 13, 2026, the average yearly pay for reinforcement learning in Washington is $66,083.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,200.00 and $77,000.00 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 Washington? The most popular types of Reinforcement Learning jobs in Washington are:
What are popular job titles related to Reinforcement Learning jobs in Washington? For Reinforcement Learning jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning jobs in Washington look for? The top searched job categories for Reinforcement Learning jobs in Washington are:
What cities in Washington are hiring for Reinforcement Learning jobs? Cities in Washington with the most Reinforcement Learning job openings:
Reinforcement Learning jobs near you
Infographic showing various Reinforcement Learning job openings in Washington as of July 2026, with employment types broken down into 2% Internship, 59% Full Time, 34% Part Time, and 5% Contract. Highlights an 100% In-person job distribution, with an average salary of $66,083 per year, or $31.8 per hour.
Machine Learning Engineer

Machine Learning Engineer

Johns Hopkins Applied Physics Laboratory

Laurel, MD • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 days ago

Johns Hopkins Applied Physics Laboratory rating

9.9

Company rating: 9.9 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

1st of 59 rated research

Job description

Description
Do you have demonstrated machine learning experience and want to apply that experience to solving a wide variety of complex problems in this rapidly evolving field?
Do you thrive in a collaborative research environment, working alongside an energetic, multidisciplinary team of scientists and engineers?
Are you ready to help the US secure and maintain leadership in the development and deployment of AI/ML algorithms for non-kinetic defense systems?
If so, we're looking for someone like you to join our team at APL!
We are seeking an experienced Machine Learning Engineer who will contribute to all phases of the machine learning algorithm development and implementation. You will be joining a team of engineers and scientists who are at the forefront of APL's mission to provide innovative solutions to critical challenges.
As a Machine Learning Engineer, you will...
  • Design, implement, and evaluate advanced machine learning algorithms to solve challenging real-world planning, perception, coordination, and control problems in support of national defense.
  • Develop software pipelines to integrate data streams, simulation environments, and intelligent decision-making algorithms.
  • Work with technologies and concepts at the cutting edge of AI, including but not limited to: deep reinforcement learning, foundation models, large language models, convolutional/recurrent/graph neural networks, computer vision, and physics-based modeling and simulation tools.
  • Collaborate closely with the talented team of scientists and engineers in our group and with others across APL.
  • Engage directly with sponsors to communicate proposed concepts, solutions, and analysis.

Qualifications
You meet the minimum requirements for the job if you...
  • Have a Bachelor's degree in Mathematics, Physics, Engineering, Computer Science, or a related field.
  • Have at least 2+ years of experience in machine learning and data science fields.
  • Have at least one year of hands-on experience applying/developing machine learning algorithms using common libraries such as PyTorch or TensorFlow.
  • Have strong foundational knowledge in at least two of the following: classification, clustering, deep learning, reinforcement learning, computer vision (object detection and visual tracking), multi-agent systems, or optimization/control theory.
  • Have demonstrated experience in working with version control software like Git.
  • Have strong, effective communication skills both verbal and written.
  • Are able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

You 'll go above and beyond our minimum requirements if you...
  • Have an MS in Mathematics, Physics, Engineering, Computer Science, or a related field.
  • Have 5+ years of experience in designing and implementing AI/ML algorithms for a variety of datasets.
  • Have proven experience applying state-of-the-art deep learning techniques to solve distributed resource allocation problems.
  • Have hands-on experience building computer vision pipelines for detection, tracking, segmentation, or multi-modal sensor fusion.
  • Have experience with modeling and simulation platforms such as AFSIM, Blender, Unity, or Unreal.
  • Are comfortable working in high performance computing environments (GPU/CPU clusters).
  • Have proficiency in one or more of the following technology areas: multi-agent reinforcement learning, geometric deep learning, multi-modal sensor fusion, agentic AI.
  • Have a track record of writing deployable, production-level code (Python, C/C++) for real-world applications.

#LI-KW1
About Us
Why Work at APL?
The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation's most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.
At APL, we celebrate our differences of perspectives and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL's campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at https://www.jhuapl.edu/careers.
All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law. APL is committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact Accessibility@jhuapl.edu.
The referenced pay range is based on JHU APL's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis.
Minimum Rate
$100,000 Annually
Maximum Rate
$245,000 Annually

What Johns Hopkins Applied Physics Laboratory employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply