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Remote Reinforcement Learning Intern Jobs in Texas

Auto Lane Corp

Machine Learning Lead

Austin, TX · On-site +1

$54.75 - $75/hr

Remote US (Bay Area, Austin preferred) About Autolane Autolane is on a mission to revolutionize ... Agent Reinforcement Learning for heterogeneous agent coordination--that enable our platform to ...

Roku

Senior Machine Learning Engineer

Austin, TX · On-site +1

$121.40K - $160K/yr

We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems and Auction ... remote work except for employees whose roles are required to be in the office five days a week or ...

Signify

Tecnical Service Intern

Milano, TX · On-site +1

$13.25 - $17.75/hr

Our culture of continuous learning, creativity, and commitment to diversity and inclusion empowers ... Hands-on exposure to remote monitoring, ticket management, and troubleshooting support. * How ...

Genlyte Group

Tecnical Service Intern

Milano, TX · On-site +1

$13.25 - $17.75/hr

Our culture of continuous learning, creativity, and commitment to diversity and inclusion empowers ... Hands-on exposure to remote monitoring, ticket management, and troubleshooting support. * How ...

Sales Tax and More

Part Time Intern

De Kalb, TX · Remote

$10 - $15/hr

Location is not important as the position is 100% remote. However, due to increasingly tough labor and tax laws, we only hire in the following states: Alabama Arizona Arkansas Indiana Kansas Kentucky ...

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Remote Reinforcement Learning Intern information

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

To thrive as a Remote Reinforcement Learning Intern, you need a strong background in mathematics, programming (especially Python), and foundational knowledge of machine learning concepts, typically demonstrated through coursework or relevant projects. Familiarity with reinforcement learning libraries (such as TensorFlow, PyTorch, or OpenAI Gym), version control systems like Git, and possibly cloud computing platforms is highly valuable. Excellent problem-solving abilities, self-motivation, and effective remote communication skills help interns excel in independent and collaborative tasks. These skills are essential for contributing to innovative research and development projects while working efficiently in a distributed team environment.

What are some common challenges faced by remote reinforcement learning interns, and how can they be overcome?

Remote reinforcement learning interns often encounter challenges related to communication and collaboration, especially when working with distributed teams. It can also be difficult to access computational resources or receive timely feedback on experiments. To overcome these challenges, it's important to proactively schedule regular check-ins with mentors, utilize collaborative tools (such as Slack or GitHub), and ensure a reliable internet connection. Additionally, keeping detailed documentation and being transparent about progress can help facilitate smoother teamwork and problem-solving.

What does a Remote Reinforcement Learning Intern do?

A Remote Reinforcement Learning Intern assists with research and development projects that focus on reinforcement learning, a type of machine learning where agents learn to make decisions by trial and error. Their tasks often include implementing algorithms, running experiments, analyzing results, and contributing to academic papers or practical applications. Working remotely, they collaborate with teams using online tools and communicate progress regularly. The role is ideal for students or recent graduates who want to gain hands-on experience in artificial intelligence and machine learning.
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What cities in Texas are hiring for Remote Reinforcement Learning Intern jobs? Cities in Texas with the most Remote Reinforcement Learning Intern job openings:
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Infographic showing various Remote Reinforcement Learning Intern job openings in Texas as of May 2026, with employment types broken down into 21% Full Time, and 79% Part Time. Highlights an 71% Physical, 28% Hybrid, and 1% Remote job distribution.

Reinforcement Learning Engineer

Bright Vision Technologies

Frisco, TX • Remote

Other

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

Job description

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications.
As we continue to grow, we’re looking for a skilled Reinforcement Learning Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
 Reinforcement Learning Engineer Job Title: Reinforcement Learning Engineer
Location: 100% Remote (Continental United States)
Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)
Experience: 6+ years
Salary: 100k - 150k
Sponsorship: No new H1B sponsorship available. H1B transfers welcomed for qualified candidates.
Employment Type: Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party)
Engagement: Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap
Compensation: Competitive base salary commensurate with experience, plus benefits.
Employment Terms & Visa Policy
This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies.
This role is part of Bright Vision Technologies’ in-house Statement of Work (SOW) engagement. The client, end customer, and employer for this position is Bright Vision Technologies — there is no third-party client, vendor, or implementation partner involved.
We do not engage in C2C, 1099, or third-party arrangements for this role.
BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING PLEASE.
Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables.
No new H1B sponsorship is available for this role.
However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates.
For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience.
Job Summary
We are looking for a Reinforcement Learning Engineer to design, train, and deploy RL-based systems for high-impact decision-making problems where supervised learning alone is insufficient. The role requires deep familiarity with modern reinforcement learning algorithms, simulation environments, reward modeling, and the engineering complexity of training and evaluating policies at scale. The ideal candidate has both research depth and engineering pragmatism, with experience taking RL solutions out of the lab and into production where stability, safety, and ongoing improvement are critical.
Key Responsibilities
  • Design and implement reinforcement learning solutions for sequential decision-making problems in real and simulated environments.
  • Develop, calibrate, and maintain simulation environments suitable for large-scale agent training.
  • Implement and evaluate modern RL algorithms including policy gradient, actor-critic, off-policy, and offline RL methods.
  • Engineer reward functions and shaping strategies that align agent behavior with desired outcomes and safety constraints.
  • Apply offline RL and imitation learning techniques where exploration is costly or unsafe.
  • Use RLHF, DPO, and related techniques for fine-tuning large language models when relevant.
  • Build scalable training infrastructure for distributed RL, including efficient experience collection and replay systems.
  • Optimize training stability and sample efficiency through algorithmic and engineering improvements.
  • Design rigorous evaluation protocols, including out-of-distribution and adversarial test cases.
  • Implement safety mechanisms such as constraint enforcement, conservative policies, and human-in-the-loop oversight.
  • Collaborate with applied scientists and product teams to identify high-value RL use cases.
  • Monitor deployed policies and models in production for drift, regression, and unintended behaviors, building the alerting and dashboards that surface issues before they meaningfully affect users.
  • Document methodology, design decisions, and operational characteristics for internal stakeholders.
  • Stay current with RL research and translate promising techniques into production-ready solutions.

Required Qualifications
  • Master’s or PhD in Computer Science, Machine Learning, or a related field; or equivalent applied experience.
  • Six or more years of combined RL research and engineering experience.
  • Strong proficiency in Python and modern deep learning frameworks.
  • Hands-on experience with at least one major RL library or in-house RL stack.
  • Solid understanding of probability, optimization, and the theoretical foundations of RL.
  • Experience designing and tuning reward functions in non-trivial environments.
  • Familiarity with simulation environments and large-scale experience collection.
  • Experience training neural network policies on GPU clusters.
  • Strong written and verbal communication skills.
  • Track record of shipping or publishing impactful RL work.

Preferred Qualifications
  • Experience with RLHF for large language models.
  • Familiarity with multi-agent RL or hierarchical RL.
  • Exposure to robotics, control systems, or autonomous driving.
  • Publications in RL or related research venues.
  • Open-source contributions to RL libraries or environments.

How to Apply
Would you like to know more about this opportunity?
For immediate consideration, please send your resume to harry@bvteck.com or contact us at (908) 676-4399. Learn more about Bright Vision Technologies at www.bvteck.com.
We recognize that our people are our strength, and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company.
We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
Bright Vision Technologies is an Equal Opportunity Employer, including Disability/Veterans.
Position offered by “No Fee Agency.”

 

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

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