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Ai Reinforcement Learning Jobs in Texas (NOW HIRING)

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. The Senior Reinforcement Learning Engineer will leverage their expertise in ...

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. The Senior Reinforcement Learning Engineer will focus on achieving ...

Apptronik

Reinforcement Learning Engineer

Austin, TX · On-site

Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in ... As a Reinforcement Learning Engineer, you will be a core contributor to the intelligence and ...

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in ... JOB SUMMARY The Senior Reinforcement Learning Engineer is a key, hands-on role focused on achieving ...

webAI

AI Research Scientist

Austin, TX · On-site

... AI, reinforcement learning, or multimodal learning • Familiarity with privacy-preserving ML techniques such as federated learning • Experience contributing to academic publications, patents, or ...

YO AI Labs

Machine Learning Engineer - Remote

Austin, TX · Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities * Create reinforcement learning environments for software engineering tasks. * Design tasks involving bug fixing, feature development ...

YO AI Labs

Machine Learning Engineer - Remote

Dallas, TX · Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities * Create reinforcement learning environments for software engineering tasks. * Design tasks involving bug fixing, feature development ...

YO AI Labs

AI Trainer - Remote

Austin, TX · Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

New

YO AI Labs

AI Engineer - Remote

Dallas, TX · Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

YO AI Labs

AI Trainer - Remote

Houston, TX · Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

New

YO AI Labs

AI Engineer - Remote

Austin, TX · Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

webAI Inc

Staff R&D AI Engineer

Austin, TX · On-site

As a Staff R&D AI Engineer, you will lead the development of cutting-edge AI systems that bridge ... Architect and implement reinforcement learning systems for sequential decision-making, including ...

YO AI Labs

AI Trainer - Remote

Dallas, TX · Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

New

YO AI Labs

AI Engineer - Remote

Houston, TX · Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

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Ai Reinforcement Learning information

What is AI reinforcement learning?

AI reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by interacting with an environment. The agent receives feedback in the form of rewards or penalties based on its actions, which it uses to improve its future performance. Reinforcement learning is widely used in applications such as robotics, game playing, recommendation systems, and autonomous vehicles. Unlike supervised learning, RL doesn't require labeled input/output pairs and learns through trial and error.

What are the key skills and qualifications needed to thrive as an AI reinforcement learning specialist?

To thrive as an AI Reinforcement Learning Specialist, you need strong expertise in machine learning, deep learning, and mathematics, usually backed by a degree in computer science, engineering, or a related field. Familiarity with programming languages like Python, frameworks such as TensorFlow or PyTorch, and experience with RL-specific libraries like OpenAI Gym are typically required. Analytical thinking, problem-solving abilities, and effective collaboration are essential soft skills for excelling in this role. These skills and qualifications are crucial for developing, optimizing, and deploying RL algorithms that solve complex, real-world problems.

What are some common challenges faced by AI reinforcement learning specialists when deploying models in real-world applications?

AI Reinforcement Learning (RL) specialists often encounter challenges such as ensuring the reliability and safety of RL agents outside of controlled environments. Real-world data can be noisy and unpredictable, making it difficult for models trained in simulations to generalize. Additionally, RL algorithms typically require significant computational resources and time for training, which can be a constraint in fast-paced projects. Collaboration with domain experts and software engineers is essential to adapt algorithms to production systems and continuously monitor performance for unexpected behaviors.

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

AspectAi Reinforcement LearningData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; knowledge of algorithmsDegree in Statistics, Data Science, or related fields; programming skills
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness analytics, data analysis teams, consulting firms
Industry UsageAI product development, autonomous systems, roboticsBusiness insights, predictive modeling, data analysis
Common Search/ComparisonYesYes

Ai Reinforcement Learning focuses on developing algorithms that enable machines to learn through trial and error to make decisions. Data Scientists analyze data to extract insights and build predictive models. While both roles require programming skills and a background in data or algorithms, reinforcement learning specialists primarily work on AI systems that learn from interactions, whereas Data Scientists focus on interpreting data to inform business decisions.

What are popular job titles related to Ai Reinforcement Learning jobs in Texas?

For Ai Reinforcement Learning jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Ai Reinforcement Learning jobs in Texas look for?

The top searched job categories for Ai Reinforcement Learning jobs in Texas are:

What cities in Texas are hiring for Ai Reinforcement Learning jobs?

Cities in Texas with the most Ai Reinforcement Learning job openings:

Ai Reinforcement Learning jobs near you
Infographic showing various Ai Reinforcement Learning job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 20% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Reinforcement Learning Engineer

Austin, TX • On-site

Apptronik
Industrial Automation Equipment Manufacturing • 11 - 50 employees
Learn more about Apptronikexternal

$103K - $142K/yr

Full-time

Re-posted 5 days ago

Job description

Job Summary:
Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. The Senior Reinforcement Learning Engineer will leverage their expertise in reinforcement learning to solve locomotion and manipulation challenges, mentor junior engineers, and implement advanced learning algorithms for the company's humanoid robots.
Responsibilities:
• Implement and deploy state-of-the-art RL algorithms to achieve ambitious, world-class performance on dynamic locomotion and manipulation tasks with physical hardware.
• Drive the entire development cycle, from prototyping in simulation to robustly transferring and fine-tuning policies on the robot.
• Optimize and scale the RL training pipeline for faster iteration, contributing to core infrastructure for high-throughput simulation and distributed training.
• Mentor junior engineers by providing technical guidance, conducting insightful code reviews, and sharing best practices in reinforcement learning and software development.
• Collaborate closely with the robotics and hardware teams to diagnose system-level issues and co-develop solutions that enable more complex learned behaviors.
• Analyze and present hardware results to guide future technical directions and demonstrate progress on key company objectives.
• Develop and refine motion retargeting pipelines to translate human demonstration data (mocap, teleoperation) into robust reference trajectories for reinforcement learning.
Qualifications:
Required:
• Deep, hands-on expertise (5+ years) with common RL frameworks (e.g., PyTorch, JAX) and high-fidelity physics simulators (e.g., MuJoCo, IsaacGym)
• Mastery of Python for rapid prototyping and training, alongside strong proficiency in C++ for developing performant, deployable code.
• Experience building or utilizing large-scale, distributed training pipelines and a strong intuition for their optimization.
• A strong theoretical understanding of modern reinforcement learning, including deep expertise in areas like imitation learning, model-based RL, and sim-to-real transfer techniques.
• A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches.
• A results-oriented mindset with a passion for seeing complex algorithms work on real-world hardware.
• A PhD or MS in Computer Science, Robotics, or a related field, with 2+ years industry experience strongly preferred.
• A proven track record of successfully deploying learning-based policies on physical robotic systems, especially legged robots or manipulators.
• Demonstrated experience mentoring or providing technical guidance to other engineers in a team environment.
• A strong publication record in relevant conferences or journals (e.g., CoRL, RSS, ICRA) is a significant plus.
Company:
Apptronik is a robotics company that designs and builds humanoid robots for various real-world applications. Founded in 2016, the company is headquartered in Austin, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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