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Senior Reinforcement Learning Jobs (NOW HIRING)

JazzX AI

Senior Staff AI Engineer

Los Altos, CA · On-site

$123K - $169K/yr

The Senior Staff AI Engineer will lead the design and development of reinforcement learning systems, ensuring they are scalable, efficient, and integrated into the company's broader AGI platform.

JazzX AI

Senior Staff AI Engineer

Los Altos, CA · On-site

$123K - $169K/yr

The Senior Staff AI Engineer will lead the design and development of reinforcement learning systems, ensuring they are scalable, efficient, and integrated into the company's broader AGI platform.

Unitytech

Senior Machine Learning Engineer

Mountain View, CA · On-site +1

$123K - $169K/yr

We're looking for a Senior Machine Learning Engineer to lead the development of these foundational ... Lead high-impact initiatives, including hierarchical reinforcement learning for scalable behaviors ...

Roku

Senior Machine Learning Engineer, Search

San Jose, CA · On-site

$361K - $510K/yr

Our systems leverage modern ML and GenAI techniques, including LLMs, reinforcement learning, multi ... About the Role We are looking for a Senior Machine Learning Tech Lead to drive ranking and ...

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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 23, 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 July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $80,287 per year, or $38.6 per hour.

Senior Staff Research Engineer - Reinforcement Learning for AI Agents

XPENG

Santa Clara, CA • On-site

$122K - $168K/yr

Full-time

Posted 6 days ago

Job description

Job Summary:
XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles. They are looking for exceptional Research Engineers / Scientists to design learning systems that allow agents to plan over long horizons and improve through experience.
Responsibilities:
• Reinforcement learning methods for LLM-driven agents and decision systems.
• Policy optimization for long-horizon reasoning and planning.
• Learning from human or AI feedback (RLHF / RLAIF).
• Agent training pipelines built on top of our agent infrastructure platform.
• Evaluation and benchmarking systems for agent capabilities.
• Learning loops that integrate real-world and simulation data.
• Contribute to AI systems that continuously improve after deployment.
Qualifications:
Required:
• MS or PhD in Computer Science, AI, Machine Learning, Robotics, or a related field.
• Strong background in reinforcement learning or machine learning.
• Experience implementing RL algorithms such as PPO, Actor-Critic, or policy gradient methods.
• Strong programming skills in Python with PyTorch or JAX.
• Experience building ML training systems or infrastructure.
Preferred:
• Experience with RLHF or preference learning.
• Experience with LLM agents or tool-using AI systems.
• Multi-agent systems or long-horizon planning.
• Simulation environments for RL.
• Publications in NeurIPS, ICML, ICLR, ACL, or related venues.
Company:
XPENG is a leading Chinese Smart EV company that designs, develops, manufactures, and markets Smart EVs that appeal to the large and growing base of technology-savvy middle-class consumers. Founded in 2014, the company is headquartered in Guangzhou, CHN, with a team of 10001+ employees. The company is currently Late Stage.

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