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Reinforcement Learning Engineer Jobs in Providence, RI

Reinforcement Learning Engineer information

See Providence, RI salary details

$38.4K

$117K

$193.5K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 29, 2026, the average yearly pay for reinforcement learning engineer in Providence, RI is $117,049.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,800.00 and $153,000.00 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 Providence, RI?

For Reinforcement Learning Engineer jobs in Providence, RI, the most frequently searched job titles are:

What job categories do people searching Reinforcement Learning Engineer jobs in Providence, RI look for?

The top searched job categories for Reinforcement Learning Engineer jobs in Providence, RI are:

Infographic showing various Reinforcement Learning Engineer job openings in Providence, RI 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 $117,050 per year, or $56.3 per hour.

Lead Decision Intelligence Engineer (AI) - NBA

Humana Inc

Providence, RI • On-site

$129 - $178/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.


Humana rating

8.0

Company rating: 8.0 out of 10

Based on 267 frontline employees who took The Breakroom Quiz

170th of 315 rated insurance


Job description

Become a part of our caring community

The Lead Decision Intelligence Engineer (AI) owns the application of Decision Intelligence and agentic AI across the NBA platform. This role analyzes and formalizes the business decisions that drive member engagement, translating stakeholder objectives, constraints, policies, and available data into structured decision models that can be evaluated, optimized, and automated. Working closely with business, product, and engineering teams, you identify where decisions should remain rule-based, where predictive models should be applied, and where agentic systems can create measurable value.

You then design and build production-grade decision intelligence capabilities that help teams create, understand, optimize, and govern member actions. Using LangGraph, LangChain, Azure OpenAI, Azure AI Foundry, Databricks, and Humana's AI Gateway, you build agentic workflows that reason through decision processes, generate recommendations, explain tradeoffs, assist with action authoring, and continuously improve decision outcomes. This is a hands-on technical leadership role that combines decision science, AI engineering, and software architecture while leading a small team of engineers.

Key Responsibilities

Decision intelligence modeling —

Decision decomposition —

Optimization strategy —

Agentic workflow delivery —

Action Library intelligence —

LLM and agent engineering —

Knowledge and retrieval systems —

Reinforcement learning integration —

Evaluation and experimentation —

AI governance and safety —

Team leadership —

Cross-functional partnership —

Use your skills to make an impact Required Qualifications

Bachelor's degree in computer science or related field

6+ years of software engineering, machine learning engineering, AI engineering, or decision intelligence experience, including at least 1–2 years in a technical leadership capacity.

Strong Python engineering experience building and operating production AI systems.

Hands‑on experience building agentic applications using LangGraph, LangChain, AutoGen, CrewAI, or similar orchestration frameworks.

Experience integrating Azure OpenAI, Azure AI Foundry, Vertex AI, Anthropic, OpenAI, or comparable enterprise AI platforms.

Strong understanding of Decision Intelligence concepts, including decision modeling, optimization, decision automation, objectives, constraints, and outcome measurement.

Experience implementing LLM application patterns including tool calling, structured outputs, retrieval‑augmented generation (RAG), memory management, and workflow orchestration.

Experience building evaluation frameworks for AI systems, including automated evaluation, human review, performance measurement, and experimentation.

Ability to map business processes into formal decision frameworks and communicate those models to both technical and non‑technical stakeholders.

Demonstrated ability to lead a small engineering team while remaining a hands‑on contributor.

Strong communication skills with the ability to explain complex AI and decision architectures to senior leadership.

Preferred Qualifications

Experience with Decision Intelligence methodologies, decision modeling notation, decision requirements analysis, influence diagrams, decision graphs, or business decision management frameworks.

Experience operationalizing reinforcement learning, contextual bandits, recommendation systems, or next‑best‑action optimization platforms.

Experience with Databricks, MLflow, Feature Store, Mosaic AI, or enterprise machine learning platforms.

Experience with Azure AI Search, vector databases, semantic retrieval systems, and enterprise knowledge architectures.

Experience with observability platforms such as LangSmith, OpenTelemetry, PromptFlow, Azure Monitor, or equivalent AI monitoring solutions.

Experience integrating AI capabilities into enterprise software platforms and workflow‑driven applications.

Familiarity with Adobe Experience Platform (AEP), Salesforce, CRM platforms, healthcare engagement platforms, or marketing technology ecosystems.

Background in healthcare, insurance, or another highly regulated industry with auditability, explainability, and compliance requirements.

Key Responsibilities Microservices & Backend Engineering
  • Architect, implement, and operate microservices that deliver:

  • Action and variant metadata

  • Context‑aware policy and eligibility evaluation

  • Versioned, read‑optimized APIs for high‑performance runtime consumption

  • Guarantee that services are:

  • Highly available, with low latency

  • Horizontally scalable for increased demand

  • Backward compatible to support safe evolution and upgrades

  • Apply industry best practices for API design, schema evolution, service isolation, and secure integration.

Database & Schema Design
  • Design, deploy, and maintain resilient database schemas to support:

  • Comprehensive action and variant catalogs

  • Versioning, lifecycle management, and effective dating

  • Rule bindings and complex metadata relationships

  • Select and operate appropriate data stores (relational, document, key‑value) tailored to workload and scalability requirements.

  • Implement and monitor:

  • Schema migration and backward compatibility strategies

  • Indexing and query optimization for performance

  • Data integrity, consistency, and reliability

  • Auditability and traceability for compliance and governance

Rules & Policy Engine Integration
  • Integrate and manage enterprise‑grade rules engines to support:

  • Eligibility, constraints, and business policies

  • Suppression, cooldowns, exclusions, and other operational guardrails

  • Policy‑driven allow/deny logic

  • Work with technologies such as Drools (DRL/DMN), IBM ODM, DMN‑based services, OPA/Rego, or similar.

  • Ensure rule execution is deterministic, versioned, stateless, and free from unintended side effects.

AI‑Assisted & Agentic Engineering
  • Utilize AI‑powered and agentic tools to:

  • Generate and refactor database schemas and service logic

  • Streamline rule authoring, validation, and ongoing refactoring

  • Detect and address conflicting or redundant rules early in the development cycle

  • Automatically produce comprehensive test cases and explore edge scenarios

  • Apply AI responsibly to reduce manual effort while safeguarding clarity, correctness, and strong governance.

Testing, Reliability & Governance
  • Develop automated tests for:

  • Database migrations and schema changes

  • Service‑level contracts and API backward compatibility

  • Rules behavior, precedence, and edge cases

  • Ensure platforms are fully observable and resilient, featuring:

  • Structured logging, metrics, and alerting

  • Clear error handling, fallback strategies, and robust incident management

  • Support audit and compliance requirements through traceable and reproducible system behavior

Collaboration & Technical Leadership
  • Work closely with platform, data, and machine learning teams to maintain clean integration points and shared standards.

  • Participate actively in architecture and design reviews to uphold platform quality.

  • Mentor junior engineers and contribute to technical standards and best practices.

Required Qualifications
  • Bachelor's degree in computer science or related field

  • 8 or more years of progressive IT experience as a senior developer in large IT projects

  • 2 or more years of project leadership experience

  • Must be passionate about contributing to an organization focused on continuously improving consumer experiences

Preferred Qualifications
  • Master's Degree
Additional Information

Work Style: Remote/Hybrid - Preferably Boston, MA. Occasional travel to Humana's offices for training or meetings may be required.

Work Hours : Typical business hours are Monday-Friday, 8 hours/day, 5 days/week-- some flexibility might be possible, depending on business needs.

Very minimal travel might be required for training, meetings, and/or conferences

Interview Format

As part of our hiring process, we will be using on-demand technology provided by Hire Vue, a third‑party vendor. This technology provides our team of recruiters and hiring managers with an enhanced method for decision‑making through on-demand candidate assessments.

If you are selected to move forward from your application prescreen, you will receive correspondence inviting you to participate in an on-demand assessment with pre-determined questions. You should anticipate the assessment to take approximately 10-15 minutes.

Your on-demand assessment will be reviewed, and you will subsequently be informed if you will be moving forward to next round of interviews.

SSN Task via Workday

Should you be extended a formal employment offer you will receive a request to enter your SSN into our Workday system to scan for duplicate profiles.

Work at Home Requirements: To ensure Home or Hybrid Home/Office employees’ ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria: At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested. In certain roles, the minimum recommended internet speed required by Humana may not be sufficient for business needs. Humana reserves the right to require associates to upgrade their internet service if necessary. Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information.

Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required.

Scheduled Weekly Hours

40

Pay Range

The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.

$129,300 - $177,800 per year

This job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance.

Description of Benefits

Humana, Inc. and its affiliated subsidiaries (collectively, “Humana”) offers competitive benefits that support whole‑person well‑being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short‑term and long‑term disability, life insurance and many other opportunities.

Application Deadline: 09-29-2026

About us

About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health – delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more atHumana.comand atCenterWell.com.

Equal Opportunity Employer

It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.

Humana complies with all applicable federal civil rights laws and does not discriminate on the basis of race, color, national origin, age, disability, sex, sexual orientation, gender identity or religion. We also provide free language interpreter services. See our https://www.humana.com/legal/accessibility-resources?source=Humana_Website.

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About Humana

Sourced by ZipRecruiter

Humana Inc., headquartered in Louisville, KY., is a leading health care company that offers a wide range of insurance products and health and wellness services that incorporate an integrated approach to lifelong well-being. By leveraging the strengths of its core businesses, Humana believes it can better explore opportunities for existing and emerging adjacencies in health care that can further enhance wellness opportunities for the millions of people across the nation with whom the company has relationships.

Industry

Health care and social assistance

Company size

10,000+ Employees

Headquarters location

Louisville, KY, US

Year founded

1961

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