ZipRecruiter

Log In

1

Reinforcement Learning Engineer Jobs in Rhode Island

Blount Fine Foods

Be Seen First

Training and Safety Instructor

Warren, RI · On-site

$23 - $26/hr

Blount Fine Foods is a family-owned and operated manufacturer, marketer, and developer of premium ... Delivers training, coaching, and reinforcement practices that drive measurable improvements in ...

All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Rhode Island

Reinforcement Learning Engineer information

See Rhode Island salary details

$37.2K

$113.5K

$187.5K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for reinforcement learning engineer in Rhode Island is $113,467.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,300.00 and $148,400.00 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 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 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 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 Rhode Island? For Reinforcement Learning Engineer jobs in Rhode Island, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Rhode Island look for? The top searched job categories for Reinforcement Learning Engineer jobs in Rhode Island are:
What cities in Rhode Island are hiring for Reinforcement Learning Engineer jobs? Cities in Rhode Island with the most Reinforcement Learning Engineer job openings:
Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Rhode Island as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $113,467 per year, or $54.6 per hour.

Research Full Stack Coder

Brown University Health

Providence, RI

$67K - $111K/yr

Other

Posted 22 days ago

Brown University Health rating

6.8

Company rating: 6.8 out of 10

Based on 71 frontline employees who took The Breakroom Quiz

492nd of 887 rated healthcare providers

Job description

Summary Brown University Health is seeking a highly motivated Full-Stack AI Developer to join a government-funded research team working at the intersection of artificial intelligence, digital health, and public health interventions. The ideal candidate will play a key role in the development and optimization of multimodal AI models, AI-driven chatbots, and agent-based modeling frameworks, contributing to research on HIV prevention, sexually transmitted infection (STI) prevention, nutrition counseling, overdose prevention, and opioid use disorder (OUD) treatment. C.A.R.E

Values Brown University Health employees are expected to successfully role model the organization's values of Compassion, Accountability, Respect, and Excellence, as these values guide our everyday actions with patients, customers, and one another. In addition to our values, all employees are expected to demonstrate the core Success Factors which tell us how we work together and how we get things done. The core Success Factors include: Instill Trust and Value Differences Patient and Community Focus and Collaborate Responsibilities AI and Software Development: Design, develop, and optimize multimodal AI models, AI-based chatbots, and modify existing agent-based modeling frameworks.

Full-Stack Engineering: Develop and maintain both front-end and back-end components of AI-driven applications, ensuring seamless user experiences. Cloud-Based Deployment: Deploy and maintain AI solutions on cloud platforms (e.g., AWS, Azure, or Google Cloud) with scalable architectures. Domain-Specific Adaptation: Learn and integrate public health knowledge in HIV prevention, STI prevention, nutrition counseling, and OUD treatment into AI-based solutions

Collaboration: Work closely with public health experts, data scientists, and researchers to refine AI models and improve application performance. Continuous Learning & Innovation: Stay updated on cutting-edge AI technologies, including large language models, reinforcement learning, and agentic frameworks. Required Qualifications Programming Expertise: Proficiency in Python, JavaScript (React/Node.js), or other full-stack technologies for AI and web applications

AI/ML Experience: Hands-on experience with machine learning frameworks (e.g., TensorFlow, PyTorch, LangChain, AutoGen). Back-End Development: Strong knowledge of API development, databases (SQL/NoSQL), and cloud computing. Front-End Development: Experience in React, Vue.js, or Angular for interactive and user-friendly applications

Cloud & DevOps: Experience in deploying AI applications on AWS, Google Cloud, or Azure, and familiarity with containerization (Docker, Kubernetes). Agent-Based Modeling: Familiarity with modifying agent-based models (ABMs) in domains such as epidemiology or public health. Ability to Learn Domain Knowledge: Strong interest and ability to understand and integrate public health concepts into AI-driven solutions.

Team Player: Ability to collaborate in a multidisciplinary research team and contribute to government-funded projects. Other Information Preferred Qualifications Bachelor's Degree or above in computer science or closely related field Experience working in health-related AI applications Knowledge of LLMs, multimodal AI, and reinforcement learning Prior work with digital health interventions How to Apply Interested candidates should submit a CV and a short cover letter through the career website and complete the application process. Applications will be reviewed on a rolling basis.

EXPERIENCE: Three to five years' experience in AI applications developing. INDEPENDENT ACTION: Performs independently within the department's policies and practices. Refers specific complex problems to the supervisor when clarification of the departmental policies and procedures is required.

SUPERVISORY RESPONSIBILITY: No direct supervisory responsibility. Trains and oversees work of Research Assistants in AI applications development. Pay Range $67,724.80 - $111,716.80 Location LHM-Providence-200 Corliss St, Suite 2 - 200 Corliss St, Suite 2 Providence, Rhode Island 02904 Work Type M-F, 8 am - 5 pm Work Shift Day Daily Hours 8 hours Driving Required No Brown University Health is committed to providing equal employment opportunities and maintaining a work environment free from all forms of unlawful discrimination and harassment

Apply

What Brown University Health employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply