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Reinforcement Learning Engineer Jobs in Pennsylvania

Cmu

Autonomy Engineer

Pittsburgh, PA · Hybrid

You have worked with tools, techniques, algorithms, software, and programming languages for deep learning, reinforcement learning, statistics, sensors and sensor fusion, planning, computer vision, or ...

Waabi

Research Scientist, Simulation Agents

Pittsburgh, PA · On-site +1

$158K - $269K/yr

Qualifications: - Masters/PhD in machine learning, computer science, engineering, or a related field. - Strong background in imitation learning and/or reinforcement learning. - Publications in top ...

Waabi

Research Scientist, Simulation Agents

Pittsburgh, PA · On-site +1

$158K - $269K/yr

Qualifications: - Masters/PhD in machine learning, computer science, engineering, or a related field. - Strong background in imitation learning and/or reinforcement learning. - Publications in top ...

aires

Artificial Intelligence Engineer

Pittsburgh, PA · Hybrid

$111K - $133K/yr

Conducts data analysis, preprocessing, training, testing, validating and feature engineering to ... unsupervised learning, reinforcement learning, and natural language processing/generation.

Duolingo

Staff AI Research Engineer

Pittsburgh, PA · On-site

$220K - $331K/yr

They will have experience at all levels of the ML stack, including feature engineering, developing training data, fine-tuning, reinforcement learning, quality evaluations, deployment, and monitoring.

Duolingo

Senior AI Research Engineer

Pittsburgh, PA · On-site

$197K - $266K/yr

They will have experience at multiple levels of the ML stack, including feature engineering, developing training data, fine-tuning, reinforcement learning, quality evaluations, deployment, and ...

Aires

Artificial Intelligence Engineer

Pittsburgh, PA · On-site

$111K - $133K/yr

Conducts data analysis, preprocessing, training, testing, validating and feature engineering to ... unsupervised learning, reinforcement learning, and natural language processing/generation.

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All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Pennsylvania

Reinforcement Learning Engineer information

See Pennsylvania salary details

$38.1K

$116.1K

$192K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for reinforcement learning engineer in Pennsylvania is $116,143.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,200.00 and $151,900.00 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 Pennsylvania?

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

What job categories do people searching Reinforcement Learning Engineer jobs in Pennsylvania look for?

The top searched job categories for Reinforcement Learning Engineer jobs in Pennsylvania are:

What cities in Pennsylvania are hiring for Reinforcement Learning Engineer jobs?

Cities in Pennsylvania with the most Reinforcement Learning Engineer job openings:

Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Pennsylvania as of August 2026, with employment types broken down into 92% Full Time, and 8% Contract. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $116,143 per year, or $55.8 per hour.

AI Engineer - Mission Innovation Lab

Software Engineering Institute

Pittsburgh, PA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of AI technologies and systems. We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security.
As our government customers adopt AI and machine learning to provide leap-ahead mission capabilities, we
  • build real-world, mission-scale AI capabilities through solving practical engineering problems

  • discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities

  • prepare our customers to be ready for the unique challenges of adopting, deploying, using, and maintaining AI capabilities

  • identify and investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape

Are you creative, curious, energetic, collaborative, technology-focused, and hard-working? Are you interested in making a difference by bringing innovation to government organizations and beyond? Apply to join our team.
Overview
As an AI Engineer who thrives at the intersection of deep-learning research and production-grade software development, you will translate cutting-edge AI concepts into robust, mission-scale solutions for the warfighting community. You will work comfortably with large-scale foundation models such as GPT and LLaMA, designing and deploying agentic workflows, as well as apply and advance traditional ML research and engineering across domains such as natural language processing, computer vision, time series forecasting, and other predictive analytics. You will collaborate closely with senior researchers, software engineers, and government sponsors to define problem statements, iterate on experimental designs, and deliver secure, reliable AI capabilities that meet stringent mission requirements.
The Mission Innovation Lab within the SEI's AI Division works with the defense and national security community to translate the "recently possible" in AI into reliable mission and warfighting capabilities.
Key Responsibilities
  • Design, develop, and fine-tune a variety of AI models.

  • Design autonomous agents and multi-step pipelines using LangChain, ReAct, tool-calling, or custom orchestration; employ the Model Context protocol to manage stateful interactions.

  • Build Retrieval-Augmented Generation pipelines that combine external knowledge bases with LLMs to improve factual accuracy for warfighting applications.

  • Implement end-to-end data pipelines, ETL processes, and back-end services (Python, C/C++, Java) that feed data to models.

  • Create CI/CD pipelines for model training, validation, containerized deployment (Docker/Kubernetes), and security scanning; maintain model registries, monitoring, and version control of context protocols.

  • Produce rapid prototypes, run benchmarks, and conduct robustness/adversarial testing in realistic environments.

  • Work closely with senior ML engineers, software developers, and government customers; mentor junior staff and contribute to design reviews and documentation.

  • Stay current with emerging LLM architectures, agentic paradigms, PEFT/LoRA methods, and AI-safety techniques; translate new research into operational capabilities.

Required Qualifications
  • Bachelor's degree in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related field with at least eight (8) years of relevant experience, or a MS degree in the same with at least five (5) years of relevant experience.

  • You will be subject to a background investigation and must be able to obtain and maintain an active Department of War (DoW) security clearance.
  • You must be able and willing to work onsite 5 days per week at an SEI office in either Pittsburgh, PA or Arlington, VA.

  • Proficiency in Python and at least one compiled language (C/C++ or Java); experience with REST/GraphQL APIs and containerization.

  • Strong grasp of ML theory (supervised, unsupervised, reinforcement learning) and evaluation metrics.

  • Hands-on experience fine-tuning LLMs and using frameworks such as Hugging Face Transformers, LangChain, or comparable agent tools.

  • Familiarity with building RAG pipelines (vector stores, dense/sparse retrievers).

  • Experience applying PEFT/LoRA methods (e.g., LoRA, adapters) to large models.

  • Understanding of Model Context protocols for managing model state across multi-turn interactions.

  • Experience building evaluation frameworks, benchmarks, or data quality pipelines

  • Experience with TensorFlow, PyTorch, or JAX; knowledge of data-pipeline tools (Airflow, Prefect, Ray) is a plus.

  • Awareness of DevSecOps practices (CI/CD, GitOps, container security scanning, model-registry concepts) is desirable.

Desired Experience
  • Deploying LLM APIs (FastAPI, gRPC) at scale, handling latency and load balancing.

  • Building multi-tool agents, planner-executor loops, or tool-calling pipelines for complex decision-making.

  • Conducting adversarial testing, implementing input sanitization, and contributing to AI-safety research.

  • Utilizing GPU/TPU resources, mixed-precision training, and distributed training frameworks such as DeepSpeed or ZeRO.

  • Prior work on defense, intelligence, or government-focused AI projects and familiarity with DoW acquisition or compliance processes.

  • Contributing to open-source AI and ML libraries, agentic frameworks, or context-protocol implementations.

Knowledge, Skills, & Abilities
  • Analytical thinking: decompose complex AI problems into tractable components and iterate rapidly.

  • Strong written and verbal communication skills for documenting designs and presenting results to technical and non-technical stakeholders.

  • Proven teamwork: collaborate in interdisciplinary groups, mentor peers, and contribute to shared codebases.

  • High curiosity and autonomy: proactively explore emerging technologies and integrate them into mission work.

Location
Arlington, VA, Pittsburgh, PA
Job Function
Software/Applications Development/Engineering
Position Type
Staff - Regular
Full time/Part time
Full time
Pay Basis
SalaryMore Information:
  • Please visit "Why Carnegie Mellon" to learn more about becoming part of an institution inspiring innovations that change the world.
  • Click here to view a listing of employee benefits
  • Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.
  • Statement of Assurance

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