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Reinforcement Learning Engineer Jobs in Texas (NOW HIRING)

Apple

Machine Learning Engineer

Austin, TX

$134K - $249K/yr

Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning ... Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ...

Apple

Machine Learning Engineer

Austin, TX

$134K - $249K/yr

Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning ... Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ...

Apple

Machine Learning Engineer

Austin, TX

$134K - $249K/yr

Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning ... Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ...

webAI Inc

Staff R&D AI Engineer

Austin, TX · On-site

Architect and implement reinforcement learning systems for sequential decision-making, including ... Collaborate with engineering teams to integrate AI models into applications and validate ...

Braze

Forward-Deployed Data Scientist II

Austin, TX · Hybrid

$98K - $164K/yr

Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms * Customer collaborator: Comfortable working ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

... Engineer. This role will assist our Online Retail Decision Automation team by helping to research ... Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning ...

Cymertek

AI/ML Engineer

San Antonio, TX · On-site

AI/ML Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note this position ... Knowledge of reinforcement learning * Familiarity with generative AI models * Experience in edge AI ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

... Engineer. This role will assist our Online Retail Decision Automation team by helping to research ... Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

... Engineer. This role will assist our Online Retail Decision Automation team by helping to research ... Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning ...

Roku

Senior Machine Learning Engineer

Austin, TX

$121K - $160K/yr

We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction ... We're looking for seasoned engineers with a background in machine learning to aid in this mission.

Apptronik

Software Engineer - Human Motion Data

Austin, TX · On-site

$113K - $136K/yr

JOB SUMMARY As a Software Engineer- Human Motion Data, you will leverage your background in robotics to build the crucial link between human-data and our reinforcement learning pipelines. This role ...

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All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Texas

Reinforcement Learning Engineer information

See Texas salary details

$35.4K

$107.9K

$178.4K

How much do reinforcement learning engineer jobs pay per year?

As of Jul 16, 2026, the average yearly pay for reinforcement learning engineer in Texas is $107,946.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,300.00 and $141,100.00 per year, depending on experience, location, and employer.

What are Reinforcement Learning Engineers?

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 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 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 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 are popular job titles related to Reinforcement Learning Engineer jobs in Texas? For Reinforcement Learning Engineer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Texas look for? The top searched job categories for Reinforcement Learning Engineer jobs in Texas are:
What cities in Texas are hiring for Reinforcement Learning Engineer jobs? Cities in Texas with the most Reinforcement Learning Engineer job openings:
Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Texas as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $107,946 per year, or $51.9 per hour.
Machine Learning Engineer, Apple Store Online

Machine Learning Engineer, Apple Store Online

Apple

Austin, TX • On-site

Full-time

Re-posted 20 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 670 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers

Job description

Imagine what you could do here! The people here at Apple don't just create products - they build the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work.
Here on the Apple Store Online team, we are responsible for Apple's largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things.
We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. You will lead the way on our Online Retail Decision Automation team by researching and developing the next generation of algorithms used to drive the Apple Online experience! This role spans central areas of our Apple Online Store including developing models for product search, recommendation systems (e.g. ranking, page generation), personalization (e.g. evidence, messaging, marketing), Generative AI and optimizing Apple-wide systems & infrastructure. As a member of the fast-paced team, you will have the outstanding and great opportunity to be part of a new projects and craft upcoming products that will delight and encourage millions of Appleʼs customers every day.
Description
To be successful, you need a strong machine learning background, proven software development skills, a love of learning, and to collaborate with cross-functional teams, including researchers, engineers, data scientists/analysts, and product managers, to develop and implement machine learning algorithms. You'll mentor other MLE's and lead an effort to build scalable end-to-end machine learning solutions for our retail customers
Minimum Qualifications
Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building highly scalable distributed systems
Hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (eg: Spark, SQL, Snowflake/Hadoop, etc)
Bachelors in a quantitative field, such as Computer Science, Applied Mathematics, Statistics, or Bachelors degree in quantitative field with a focus on AI in coursework
Preferred Qualifications
Understanding of machine learning model lifecycle from prototyping, feature engineering, training, inference, deployment, monitoring and continuous improvements via deep analysis)
Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture
Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real applications a plus
Experience with Spark, TensorFlow, Keras, and PyTorch a plus
Skilled in communication, problem solving, strategic thinking

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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