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Senior Reinforcement Learning Jobs (NOW HIRING)

Jobgether

$80K - $110K/yr

Research and apply reinforcement learning, imitation learning, and learning-from-demonstration ... The ideal candidate is a senior machine learning professional with strong research experience and ...

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $180K/yr

Our internal platform uses the same reinforcement learning toolkits that power self-driving ... senior engineers. * Train control models, track and interpret their performance, and dig into why a ...

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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 Aug 12, 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 August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $80,287 per year, or $38.6 per hour.

Senior Staff Software Engineer, AI Model Lifecycle

Crusoe

San Francisco, CA • On-site

$144K - $190K/yr

Full-time

Re-posted 19 days ago

Job description

Job Summary:
Crusoe is on a mission to accelerate the abundance of energy and intelligence, operating as a vertically integrated AI infrastructure company. The Senior Staff Software Engineer for the AI Model Lifecycle team will manage fine-tuning systems for large foundation models and implement end-to-end training pipelines for Large Language Models, contributing to the development of a comprehensive managed platform for application development lifecycle.
Responsibilities:
• Manage fine-tuning systems for large foundation models (SFT, PEFT, LoRA, adapters), including multi-node orchestration, checkpointing, failure recovery, and cost-efficient scaling.
• Implement and maintain end-to-end training pipelines for Large Language Models.
• RFT and Reinforcement learning to the fine tuning and training sections
• Distillation and reinforcement learning pipelines (e.g., preference optimization, policy optimization, reward modeling).
• Dataset, model, and experiment management: versioning, lineage, evaluation, and reproducible fine-tuning at scale.
Qualifications:
Required:
• Advanced degree in Computer Science, Engineering, or a related field.
• 8+ years of industry experience leading and driving impactful projects in the AI Space
• Experience in Generative AI (Large Language Models, Multimodal).
• Hands-on experience training, fine-tuning, and aligning LLMs using Reinforcement Learning and Reinforcement Fine-Tuning (RFT) techniques.
• Proactive and collaborative approach with the ability to work autonomously
• Passion for building cutting-edge AI products and solving challenging technical problems.
Preferred:
• Proficiency in Golang or Python for large-scale, production-level services and PyTorch
• Contributions to open-source AI projects such as vLLM or similar frameworks.
• Performance optimizations on GPU systems and inference frameworks.
Company:
Crusoe is a vertically integrated AI infrastructure company that builds and operates data centers powered by energy sources. Founded in 2018, the company is headquartered in Denver, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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