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Senior Reinforcement Learning Jobs (NOW HIRING)

Elevance Health

Research Scientist Senior

Indianapolis, IN · On-site

$94K - $120K/yr

Research Scientist Senior Research Scientist Senior This role requires associates to be in-office ... Develops scalable machine learning and reinforcement learning systems that improve healthcare ...

Elevance Health

Research Scientist Senior

Indianapolis, IN · On-site +1

$94K - $120K/yr

Research Scientist Senior Research Scientist Senior This role requires associates to be in-office ... Develops scalable machine learning and reinforcement learning systems that improve healthcare ...

Elevance Health

Research Scientist Senior

Atlanta, GA · On-site +1

$94K - $120K/yr

Research Scientist Senior Research Scientist Senior This role requires associates to be in-office ... Develops scalable machine learning and reinforcement learning systems that improve healthcare ...

Elevance Health

Research Scientist Senior

Chicago, IL · On-site +1

$101K - $129K/yr

Research Scientist Senior Research Scientist Senior This role requires associates to be in-office ... Develops scalable machine learning and reinforcement learning systems that improve healthcare ...

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Senior Reinforcement Learning information

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$25K

$80.3K

$163.5K

How much do senior reinforcement learning jobs pay per year?

As of Jul 3, 2026, the average yearly pay for senior reinforcement learning in the United States is $80,287.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,500.00 and $103,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Senior Reinforcement Learning professionals when deploying models in real-world environments?

Senior Reinforcement Learning professionals often encounter challenges such as ensuring model robustness when transferring algorithms from simulated to real-world environments, handling limited or noisy data, and managing the computational demands of training complex models. Additionally, safety and interpretability are critical, as real-world deployments can have significant impacts if models behave unpredictably. Close collaboration with domain experts and engineering teams is essential to address these challenges and ensure successful, scalable deployments.

What are the key skills and qualifications needed to thrive as a Senior Reinforcement Learning Engineer, and why are they important?

To thrive as a Senior Reinforcement Learning Engineer, you need deep expertise in machine learning, reinforcement learning algorithms, and programming languages such as Python, often supported by an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and RL-specific libraries, as well as experience with high-performance computing and cloud platforms, is typically required. Strong problem-solving abilities, collaboration, and communication skills help distinguish top performers in this role. These skills ensure the development of efficient, robust RL models and effective teamwork on complex AI projects.

What is the difference between Senior Reinforcement Learning vs Data Scientist?

AspectSenior Reinforcement LearningData Scientist
Required CredentialsAdvanced degrees in CS, ML, or related fields; experience with RL frameworksDegree in CS, Statistics, or related; strong analytical skills
Work EnvironmentResearch labs, AI teams, tech companies focusing on ML projectsBusiness analytics, data analysis, and modeling in various industries
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, marketing, tech, and more

While both roles require strong analytical skills and technical knowledge, Senior Reinforcement Learning specialists focus on developing RL algorithms and models, often in AI research settings. Data Scientists analyze data to inform business decisions across industries. The roles overlap in data handling and programming but differ in their core focus and application areas.

What does a Senior Reinforcement Learning Engineer do?

A Senior Reinforcement Learning Engineer designs, develops, and implements advanced machine learning algorithms that enable systems to learn optimal behaviors through trial and error. They work on complex problems such as robotics, game AI, recommendation systems, and automated decision-making. In addition to coding and model development, they often lead research initiatives, collaborate with cross-functional teams, and mentor junior engineers. Their role requires deep knowledge of reinforcement learning theory, practical experience with machine learning frameworks, and strong programming skills.
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Senior Reinforcement Learning jobs near you
Infographic showing various Senior Reinforcement Learning job openings in the United States as of June 2026, with employment types broken down into 17% Full Time, and 83% Part Time. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $80,287 per year, or $38.6 per hour.
Senior Engineering Manager, Reinforcement Learning Environments (RLE)

Senior Engineering Manager, Reinforcement Learning Environments (RLE)

Handshake

San Francisco, CA • On-site

Full-time

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

Job description

Job Summary:
Handshake is the career network for the AI economy, connecting knowledge workers with educational institutions and employers. The Senior Engineering Manager will lead the Reinforcement Learning Environments team, focusing on building interactive sandboxes for training AI models and ensuring system reliability and data quality.
Responsibilities:
• Lead, hire, and develop a high-performing team building RL environments and the platform behind them
• Own the RLE roadmap and execution in close partnership with Research, Product, and Operations
• Drive architecture for scalable, reliable, extensible environment systems and data generation pipelines
• Build modular, plug-and-play domains that integrate cleanly with training and evaluation loops
• Raise the bar on reliability, observability, performance, and data quality
• Create a culture of ownership, speed, and strong engineering fundamentals in an ambiguity heavy setting
Qualifications:
Required:
• 3+ years managing teams
• 5+ years hands-on engineering experience
• Experience leading senior engineers
• Proven ability to align cross-functionally and deliver in fast-moving, unclear problem spaces
• Strong platform/distributed systems background
• Ability to turn research/ops needs into a clear roadmap, ship iteratively, and measure outcomes
Preferred:
• Managing an EM (or equivalent scope) is a plus
• Experience with RL training infrastructure, simulation systems, or evaluation platforms
• Human-in-the-loop systems (annotation, rubric tooling, QA pipelines, workflow platforms)
• Operations-heavy, tech-enabled environment experience
• Familiarity with AWS/GCP, APIs, Docker, and modern stacks (TypeScript/Node, React)
• Experience building systems used by applied ML or AI research teams
Company:
Handshake is a college career network that helps students and recent graduates find their next opportunity. Founded in 2014, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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