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Reinforcement Learning Engineer Jobs in Massachusetts

Senior Machine Learning Engineer, Data Mining

Boston, MA ยท On-site +1

$133K - $175K/yr

Reinforcement Learning for Data Discover : Build RL-based policy learning and reasoning systems for ... Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for ...

Senior Machine Learning Engineer, Data Mining

Boston, MA ยท On-site +1

$133K - $175K/yr

Reinforcement Learning for Data Discover : Build RL-based policy learning and reasoning systems for ... Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for ...

Senior Machine Learning Engineer, Data Mining

Boston, MA ยท On-site +1

$133K - $175K/yr

Reinforcement Learning for Data Discover : Build RL-based policy learning and reasoning systems for ... Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for ...

Software Machine Learning Engineer

Reading, MA ยท On-site

$116K - $186K/yr

Opportunity Overview As a Machine Learning Engineer, you will design, develop, and deploy applied ... Build and experiment with reinforcement learning algorithms (e.g., policy gradients, PPO, Q ...

Senior Machine Learning Engineer

Wellesley, MA ยท On-site

$111K - $222K/yr

Strong background in one or more of the following: reinforcement learning, causal inference, LLM ... Solid backend engineering skills in Python, including APIs and data modeling * A/B testing and ...

Senior Robot Learning Engineer

Boston, MA ยท On-site

$144K - $198K/yr

Senior Robot Learning Engineer The Dexterous AI Group (DAG) is looking for Robot Learning Engineers ... Reinforcement Learning and Imitation Learning for manipulation. * Planning and control algorithms ...

Senior Robot Learning Engineer The Dexterous AI Group (DAG) is looking for Robot Learning Engineers ... Reinforcement Learning and Imitation Learning for manipulation. * Planning and control algorithms ...

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Showing results 1-20

Reinforcement Learning Engineer information

See Massachusetts salary details

$41.5K

$126.5K

$209.1K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 3, 2026, the average yearly pay for reinforcement learning engineer in Massachusetts is $126,538.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,600.00 and $165,500.00 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 cities in Massachusetts are hiring for Reinforcement Learning Engineer jobs? Cities in Massachusetts with the most Reinforcement Learning Engineer job openings:
Infographic showing various Reinforcement Learning Engineer job openings in Massachusetts as of July 2026, with employment types broken down into 71% Full Time, and 29% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $126,538 per year, or $60.8 per hour.

Machine Learning / Reinforcement Learning Infrastructure Engineer

Eka Robotics

Cambridge, MA โ€ข On-site

$118K - $155K/yr

Full-time

Re-posted 6 hours ago


Job description

Job Summary:
Eka Robotics is on a mission to build intelligence for the physical world through advanced robotics. They are seeking a Reinforcement/Machine Learning Infrastructure Engineer to design, implement, and maintain large-scale model training systems that will enhance their robotics research and deployment efforts.
Responsibilities:
โ€ข Own Training Infrastructure: Design, implement, and maintain robust systems for large-scale model training, including job orchestration, scheduling, checkpointing, and experiment tracking.
โ€ข Developer Experience & Tooling: Build streamlined, intuitive abstractions for launching, monitoring, debugging, and reproducing experiments, minimizing friction and maximizing productivity for our research teams.
โ€ข Scale Distributed Training: Work closely with researchers to reliably scale reinforcement learning and machine learning pipelines across compute clusters.
โ€ข Resource Management: Ensure efficient allocation and utilization of cloud-based compute resources while building the foundational systems needed for future scaling.
โ€ข Collaborate with Researchers: Partner with the research team to understand their needs, build infrastructure that supports cutting-edge methods, guide best practices for training at scale, and contribute to core JAX model and training code.
Qualifications:
Required:
โ€ข BS, MS or higher in Computer Science, Computer Engineering, Machine Learning or a related technical field.
โ€ข Strong software engineering fundamentals with a proven track record of building ML training infrastructure, internal developer platforms, or scalable systems.
โ€ข Hands-on experience with large-scale training using JAX (preferred), PyTorch, or TensorFlow.
โ€ข Familiarity with distributed training, multi-host setups, data pipelines, and managing workloads on cloud platforms or orchestration systems (e.g., Kubernetes, SLURM, GCP, AWS).
โ€ข Strong cross-functional communication skills, a deep ownership mindset, and a passion for building tools that improve the developer experience.
โ€ข Experience building automated testing pipelines, CI/CD for ML workflows, and custom logging/telemetry stacks.
Preferred:
โ€ข Background in robotics, reinforcement learning or other machine learning systems.
โ€ข Experience designing abstractions that balance researcher flexibility with system reliability.
Company:
Founded in , the company is headquartered in Cambridge, MA, US, , with a team of 11-50 employees. The company is currently Early Stage.