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Reinforcement Learning Engineer Jobs in Miami, FL

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$36.3K

$110.8K

$183.2K

How much do reinforcement learning engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for reinforcement learning engineer in Miami, FL is $110,818.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,400.00 and $144,900.00 per year, depending on experience, location, and employer.

What is a reinforcement learning engineer?

Reinforcement Learning Engineers are specialized professionals who design, develop, and implement algorithms based on reinforcement learning, a type of machine learning where agents learn to make decisions by receiving rewards or penalties. They work on building models that enable machines to learn optimal actions through trial and error in complex environments. Their responsibilities often include developing RL architectures, tuning hyperparameters, running simulations, and applying RL methods to real-world problems like robotics, gaming, or recommendation systems. RL Engineers typically have strong backgrounds in computer science, mathematics, and deep learning, along with experience in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are some common challenges faced by reinforcement learning engineers when deploying models in real-world environments?

One of the main challenges Reinforcement Learning (RL) Engineers face is bridging the gap between simulation and real-world deployment. Models that perform well in controlled environments may struggle with unpredictable data, safety constraints, or limited feedback in production. Additionally, RL algorithms often require significant computational resources and careful tuning to avoid instability. Collaboration with domain experts and software engineers is essential to address these issues and ensure successful integration of RL solutions into existing systems.

What are the key skills and qualifications needed to thrive as a reinforcement learning engineer, and why are they important?

To thrive as a Reinforcement Learning Engineer, you need a strong background in machine learning, mathematics (especially probability and statistics), and programming languages like Python, often supported by a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like OpenAI Gym), and cloud computing platforms is typically required. Problem-solving skills, creativity, and effective collaboration help set outstanding engineers apart in this field. These competencies enable the design and deployment of advanced RL solutions that address real-world challenges and drive innovation.

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

AspectReinforcement Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's in CS, AI, or related; experience with RL frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on RL applicationsTech companies, data-driven firms, AI departments across industries
Industry UsageSpecialized in RL projects like robotics, game AI, autonomous systemsBroader applications including predictive modeling, NLP, computer vision

Reinforcement Learning Engineers focus on developing algorithms that learn through interactions with environments, often in robotics or gaming. Machine Learning Engineers work on a wider range of models and applications. While both roles require strong programming and math skills, RL Engineers specialize in sequential decision-making, whereas ML Engineers handle diverse data-driven tasks across industries.

What are popular job titles related to Reinforcement Learning Engineer jobs in Miami, FL?

For Reinforcement Learning Engineer jobs in Miami, FL, the most frequently searched job titles are:

What job categories do people searching Reinforcement Learning Engineer jobs in Miami, FL look for?

The top searched job categories for Reinforcement Learning Engineer jobs in Miami, FL are:

What cities near Miami, FL are hiring for Reinforcement Learning Engineer jobs?

Cities near Miami, FL with the most Reinforcement Learning Engineer job openings:

Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Miami, FL as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $110,818 per year, or $53.3 per hour.

Part-Time Lecturer - Applied Machine Intelligence (Miami)

Northeastern University

Miami, FL • On-site

Part-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 days ago

Job description

About the Opportunity
The College of Professional Studies at Northeastern University invites applications for a non-tenure track part time faculty lecturer in Applied Machine Intelligence on the Miami campus.
The College of Professional Studiesis one of ten colleges of Northeastern University, a nationally ranked private research university. Founded in 1960, the College provides lifelong experiential learning that unleashes the capacities of aspiring individuals in all stages and walks of life. The College teaches undergraduate, graduate, and doctoral students on campus and online in more than 90 programs.
Northeastern University will not provide H-1B, TN, O-1, E-3, or any other type of employment visa sponsorship for the successful applicant to this position, now or in the future. Furthermore, the successful applicant must be able to maintain valid work authorization in the United States throughout the entire appointment without Northeastern University's sponsorship for a visa.
Responsibilities
Qualified candidates must be prepared to work with global student populations.
The Master of Professional Studies in Applied AI is looking for part-time faculty to teach courses across the program with special emphasis on applied artificial intelligence, machine learning, natural language processing, computer vision, and experiential learning addressing business and technical challenges in industry.
Instructional areas include, but are not limited to:
  • Core AI courses: Applied Artificial Intelligence, Applied Machine Learning, Applied Natural Language Processing, Applied Computer Vision
  • Specialized areas: Deep Learning, Generative AI, Prompt Engineering, Conversational AI and Chatbots, Reinforcement Learning
  • Applied domains: Machine Learning for Cybersecurity, AI for 3D Imaging, Recommender Systems, Quantum AI, Blockchain AI, AI for Autonomous Systems
  • Foundational courses (for Connect pathway students): Python programming, Mathematical Concepts, Research Methods and Scientific Writing

The Applied AI degree is a multi-disciplinary, experience-based program that prepares professionals from diverse backgrounds to harness the transformative potential of artificial intelligence. Through courses and projects that focus on applied machine learning, AI implementation, ethical AI practices, and real-world applications, students learn to create AI solutions across manufacturing, healthcare, finance, and other industries. The program emphasizes accessibility, offering pathways for both technical and non-technical professionals to transition into AI-focused roles.
Qualifications
Minimum qualifications:
  • Terminal degree (Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or an aligned discipline
  • Demonstrated professional experience implementing AI/ML solutions in industry settings
  • Proficiency in Python and modern AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, or similar)

Strongly preferred:
  • 5+ years of professional experience in AI/ML development, implementation, or strategy roles
  • Demonstration of teaching, coaching, and/or training experience with a history of successful teaching (online/on-ground) at the graduate level strongly preferred
  • Experience teaching adult learners or working professionals
  • Expertise in one or more specialized areas: natural language processing, computer vision, generative AI, deep learning, conversational AI, reinforcement learning, or AI applications in specific domains (cybersecurity, 3D imaging, autonomous systems)
  • Understanding of AI ethics, governance, and responsible AI practices
  • Ability to make complex AI concepts accessible to learners from diverse academic backgrounds

Application Materials
Applicants should submit materials including a cover letter and vitae.
Successful faculty at Northeastern will be dynamic and innovative scholars with a record of teaching excellence and a commitment to fostering belonging in the university community. Thus, strong candidates for this faculty position will have the expertise, knowledge, and skills to build their pedagogy, and curriculum in ways that reflect and enhance this commitment. Please indicate how your expertise, knowledge, and skills have prepared you to contribute to this work in your cover letter.
Please direct questions to John Wilder at j.wilder@northeastern.edu.
Application will be reviewed until the position is filled.
Position Type
Academic
Additional Information
Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.
Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more information.
All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law.
Pay Range:
The per credit rate for this position is $1,569.00.

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