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Reinforcement Learning Engineer Jobs in Delaware

Athenago

AI Engineering Intern

Wilmington, DE

Familiarity with concepts like reinforcement learning, prompt engineering for LLMs, or building multi-agent systems. * Experience with data preprocessing pipelines, and working with datasets relevant ...

Athena LLC

Familiarity with concepts like reinforcement learning, prompt engineering for LLMs, or building multi-agent systems. * Experience with data preprocessing pipelines, and working with datasets relevant ...

Chase

AWS Software Engineer III-ETL/AI

Wilmington, DE · On-site

Experience with reinforcement learning, prompt engineering, or agent-based simulation, especially where it improves agent reliability and business outcomes * Exposure to modern front-end technologies ...

Chase

AWS Software Engineer III-ETL/AI

Newark, DE · On-site

Experience with reinforcement learning, prompt engineering, or agent-based simulation, especially where it improves agent reliability and business outcomes * Exposure to modern front-end technologies ...

Dexian

DE · On-site

$122K - $161K/yr

Familiarity with Prompt Engineering for agents/assistants, Supervised Fine-Tuning (SFT), Reinforcement Learning with Human Feedback (RLHF), RAG, and HITL in Agentic Ecosystems. * Knowledge of AI/LLM ...

Sallie Mae

Senior Manager, Statistical Modeling

Newark, DE · On-site

$85K - $104K/yr

... reinforcement learning). * Experience with cloud-based platforms (e.g., AWS, Azure, Google Cloud). * Familiarity with data engineering, data visualization, and model evaluation techniques.

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How much do reinforcement learning engineer jobs pay per year?

As of Jul 7, 2026, the average yearly pay for reinforcement learning engineer in Delaware is $115,964.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,100.00 and $151,600.00 per year, depending on experience, location, and employer.

What are Reinforcement Learning Engineers?

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 Delaware? For Reinforcement Learning Engineer jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Delaware look for? The top searched job categories for Reinforcement Learning Engineer jobs in Delaware are:
What cities in Delaware are hiring for Reinforcement Learning Engineer jobs? Cities in Delaware with the most Reinforcement Learning Engineer job openings:
Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Delaware as of July 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $115,964 per year, or $55.8 per hour.

AI Engineering Intern

Athenago

Wilmington, DE

Full-time

Re-posted 29 days ago

Job description

At Athena, we empower possibility through transformative delegation. Our mission is to build the world's premier delegation platform, combining the strengths of exceptional Executive Assistants with advanced AI technologies to save our clients millions of hours each year.

Role Overview

The AI Engineer Intern will develop and enhance Large Language Models (LLMs) to improve task delegation workflows, instruction generation, and automate agentic processes. This role will also contribute to building and improving AI agentic systems that can reason through tasks, use tools, and support more reliable task execution across Athena workflows. You will play a crucial role in prototyping, developing, and deploying cutting-edge AI features that directly impact client productivity and efficiency.

Responsibilities

  • Assist in developing and fine-tuning large language models (LLMs) to better understand and generate instructions for complex tasks. You'll experiment with model parameters and training data to improve performance.

  • Build and integrate AI-driven features that improve task delegation workflows - for example, creating intelligent agents that break down client requests into actionable steps for our team.

  • Collaborate with senior AI engineers to prototype systems that use AI for agentic workflows, enabling the platform to automatically handle or delegate routine instructions.

  • Support the development of AI agentic components such as task planning, tool use, memory, prompt workflows, and orchestration logic to help agents operate more effectively in real-world scenarios.

  • Evaluate model outputs for accuracy and usefulness. Develop tests and metrics to assess how well the AI-generated instructions or recommendations are performing in real-world scenarios.

  • Help build lightweight evaluation harnesses and experiments to test agent behavior, workflow reliability, and the quality of AI-generated task execution.

  • Work cross-functionally with product and software engineers to implement AI solutions into the Athena platform. Communicate technical findings and iterate on solutions based on user feedback.

Qualifications

  • Currently pursuing (or recently completed) a degree in Computer Science, Stats, or related field, with coursework in machine learning or artificial intelligence.

  • Strong programming abilities in Python (and familiarity with ML libraries like TensorFlow, PyTorch). Comfortable with data structures, algorithms, and writing clean, efficient code.

  • Solid understanding of machine learning fundamentals and algorithms (classification, NLP, Deep Learning). Familiarity with concepts of training, fine-tuning, and evaluating models.

  • Knowledge of natural language processing techniques. Understanding how large language models work and experience using or implementing NLP models.

  • Interest in AI agentic systems, including areas such as prompt design, tool use, workflow orchestration, multi-step reasoning, or evaluation of LLM-based systems.

  • Ability to break down complex problems and experiment with creative AI solutions. Eagerness to learn new technologies and frameworks quickly.

Preferred Qualifications

  • Previous projects or internship experience involving machine learning or AI (especially work with LLMs or NLP projects).

  • Experience with ML ops or model deployment (e.g. using cloud AI services, Docker, REST APIs for model serving).

  • Familiarity with concepts like reinforcement learning, prompt engineering for LLMs, or building multi-agent systems.

  • Experience with data preprocessing pipelines, and working with datasets relevant to language models or automation tasks.

  • Exposure to agent evaluation, prompt pipelines, orchestration frameworks, or AI systems that interact with external tools or APIs is a plus.

  • Awareness of the latest trends and research in AI/ML (new model architectures, papers, etc.), showing a passion for staying up-to-date in the field.

Benefits

  • You will be mentored by Athena's AI and software engineering experts. They will provide guidance, code reviews, and support as you work on challenging AI projects, ensuring you learn best practices in the field.

  • Expect to engage with cutting-edge AI technology. You'll contribute to pioneering projects (like improving AI-driven delegation) that could become core Athena offerings, giving you tangible achievements to highlight in your career.

  • Be part of a collaborative, forward-thinking team. Interns at Athena are included in all aspects of company life - from daily stand-ups to social outings - receiving the same respect and perks as full-timers.

  • This internship will enhance your practical AI skills and professional network. You'll leave with a deeper understanding of how AI can automate and improve real-world processes, and you may earn opportunities for future employment at Athena.com based on your performance.

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