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Reinforcement Learning Engineer Jobs in Tomball, TX

Senior Machine Learning Engineer

Houston, TX ยท On-site

$99K - $137K/yr

Senior Machine Learning Engineer Location: Houston, TX Environment: Standard, 5-days onsite : Must ... Experience with Reinforcement Learning, RAG (Retrieval-Augmented Generation), and Agentic AI.

Lead Machine Learning Engineer

Houston, TX ยท On-site +1

$97K - $128K/yr

Build and maintain Retrieval-Augmented-Generation (RAG) systems, Reinforcement Learning frameworks ... Establish prompt engineering and data management best practices for transparency and governance.

Lead Machine Learning Engineer

Houston, TX ยท On-site +1

$97K - $128K/yr

Build and maintain Retrieval-Augmented-Generation (RAG) systems, Reinforcement Learning frameworks ... Establish prompt engineering and data management best practices for transparency and governance.

Lead Machine Learning Engineer

Houston, TX ยท Remote

$104K - $138K/yr

Build and maintain Retrieval-Augmented-Generation (RAG) systems, Reinforcement Learning frameworks ... Establish prompt engineering and data management best practices for transparency and governance.

Autonomy Engineer

Houston, TX ยท On-site

$99K - $137K/yr

Senior Autonomy Engineer Department: Software Reports To: Behavior Coordination Lead Employment ... Experience with NVIDIA Isaac Lab for reinforcement learning environment setup and training

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Reinforcement Learning Engineer information

See Tomball, TX salary details

$36K

$109.7K

$181.3K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for reinforcement learning engineer in Tomball, TX is $109,692.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,600.00 and $143,400.00 per year, depending on experience, location, and employer.

What is a reinforcement learning engineer?

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 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 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 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 near Tomball, TX are hiring for Reinforcement Learning Engineer jobs?

Cities near Tomball, TX with the most Reinforcement Learning Engineer job openings:

Infographic showing various Reinforcement Learning Engineer job openings in Tomball, TX as of June 2026, with employment types broken down into 76% Full Time, 19% Part Time, and 5% Temporary. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $109,692 per year, or $52.7 per hour.

Senior Machine Learning Engineer - Deep & Reinforcement Learning

Kanak Elite Services Inc

Houston, TX โ€ข On-site

$99K - $137K/yr

Contractor

Re-posted 6 days ago


Job description

Hello There,

My name is Himanshu Sharma, and I serve as the Recruitment Lead at Kanak-IT INC. I am reaching out to share an excellent career opportunity for the role of Senior Machine Learning Engineer with our esteemed client. If you are interested then please share your updated resume at Himanshu01@kanakits.com .

Job Description

Position           : Senior Machine Learning Engineer – Deep & Reinforcement Learning

Location          : Houston, TX Onsite

Duration         : Long term contract

Required skills:
- Degree in STEM field, Ph.D preferred.
- Master in Deep Learning, Reinforcement Learning, and multimodal large language model.
- Strong Pytorch or TensorFlow programming
- Machine Learning and Statistical Modelling - Mastery
- Exploratory Analysis
- Core Programming Skills & Languages
- AI Engineering Essentials
- DevOps and Agile
- Cloud deployment frameworks, infrastructure, and tooling