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Reinforcement Learning Engineer Jobs in Austin, TX

Senior Machine Learning Engineer

Austin, TX ยท On-site

$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.

Frontend Developer - Remote

Austin, TX ยท Remote

$80 - $120/hr

... Engineer Job Type: Contractor (~15 hours/week) Location: Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning ...

Backend Developer - Remote

Austin, TX ยท Remote

$80 - $120/hr

... Engineer Job Type: Contractor (~15 hours/week) Location: Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning ...

... with Reinforcement Learning (RL), Prompt Engineering, and Knowledge Graphs to improve AI agent capabilities. โ€ข Collaborate with cross-functional teams to integrate AI-powered solutions into ...

Create reinforcement learning environments for software engineering tasks. * Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic ...

Create reinforcement learning environments for software engineering tasks. * Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic ...

Senior Machine Learning Engineer, DevOps/SRE

Austin, TX ยท On-site

$128K - $165K/yr

We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction ... About the role We are seeking a talented and experienced Senior Software Engineer, MLOps/DevOps, to ...

By hiring incredible engineers, we drive precision. And through our collaborative process, we build ... Experience with Deep neural networks and reinforcement learning is a plus Solid math background and ...

AI/ML Engineer It is critical that the candidate has solid experience in Classical ML, GenAI ... Experience with the full LLM lifecycle including pre-training, SFT, and Reinforcement Learning ...

AI/ML Engineer It is critical that the candidate has solid experience in Classical ML, GenAI ... Experience with the full LLM lifecycle including pre-training, SFT, and Reinforcement Learning ...

AI Trainer - Remote

Austin, TX ยท Remote

$80 - $120/hr

Create reinforcement learning environments for software engineering tasks. * Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic ...

AI Technical Trainer - Remote

Austin, TX ยท Remote

$80 - $120/hr

Create reinforcement learning environments for software engineering tasks. * Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic ...

Senior Compiler Engineer - AI

Austin, TX

$121K - $160K/yr

The ideal candidate brings broad experience across machine learning, including reinforcement ... Collaborate with world-class engineers to shape next-generation compiler capabilities that power ...

Senior Compiler Engineer - AI

Austin, TX ยท On-site

$121K - $160K/yr

The ideal candidate brings broad experience across machine learning, including reinforcement ... Collaborate with world-class engineers to shape next-generation compiler capabilities that power ...

Senior Compiler Engineer - AI

Austin, TX ยท On-site

$121K - $160K/yr

The ideal candidate brings broad experience across machine learning, including reinforcement ... Collaborate with world-class engineers to shape next-generation compiler capabilities that power ...

Showing results 41-60

Reinforcement Learning Engineer information

See Austin, TX salary details

$37.7K

$114.8K

$189.8K

How much do reinforcement learning engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for reinforcement learning engineer in Austin, TX is $114,845.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,300.00 and $150,200.00 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 are popular job titles related to Reinforcement Learning Engineer jobs in Austin, TX?

For Reinforcement Learning Engineer jobs in Austin, TX, the most frequently searched job titles are:

What cities near Austin, TX are hiring for Reinforcement Learning Engineer jobs?

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

Infographic showing various Reinforcement Learning Engineer job openings in Austin, TX as of August 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 79% In-person, and 21% Remote job distribution, with an average salary of $114,845 per year, or $55.2 per hour.

Senior Machine Learning Engineer

Roku

Austin, TX โ€ข On-site

$121K - $160K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 22 days ago


Job description

Teamwork makes the stream work.
Roku is changing how the world watches TV
Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers.
From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines.
About the team
The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers, and Roku. The systems and solutions span multiple disciplines and technologies to perform real-time multi-objective optimization across distributed systems at large scale and with low latency. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation, and Inference Platform that powers the entire landscape, which we continuously evolve over time.
About the role
We're on a mission to build cutting-edge advertising technology that empowers businesses to run sustainable and highly-profitable campaigns. The Ad Performance team owns server technologies, data, and cloud services aimed at improving the ad experience. We're looking for seasoned engineers with a background in machine learning to aid in this mission. Examples of problems include improving ad relevance, inferring demographics, yield optimization, and many more. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning using both general purpose software and statistical languages.
What you'll be doing
  • ML infrastructure: Help build a first-class machine learning platform from the ground up which manages the entire model lifecycle - feature engineering, model training, versioning, deployment, online serving/evaluation, and monitoring prediction quality
  • Data analysis and feature engineering: Apply your expertise to identify and generate features that can be leveraged by multiple use cases and models
  • Model training with batch and real-time prediction scenarios: Use machine learning and statistical modelling techniques such as Decision Trees, Logistic Regression, Neural Networks, Bayesian Analysis and others to develop and evaluate algorithms for improving product/system performance, quality, and accuracy
  • Production operations: Low-level systems debugging, performance measurement, and optimisation on large production clusters
  • Collaboration with cross-functional teams: Partner with product managers, data scientists, and other engineers to deliver impactful solutions
  • Staying ahead of the curve: Continuously learn and adapt to emerging technologies and industry trends

We're excited if you have
  • Bachelors, Masters, or PhD in Computer Science, Statistics, or a related field
  • 5 years of experience in applied machine learning on real use cases
  • Proficient coding skills and strong software development experience in Spark, Python, or Java
  • Familiarity with real-time evaluation of models with low latency constraints
  • Familiarity with distributed ML frameworks such as Spark-MLlib, TensorFlow, etc.
  • Ability to work with large scale computing frameworks, data analysis systems, and modelling environments i.e. Spark, Hive, NoSQL stores such as Aerospike and ScyllaDB
  • Ad Tech experience is preferred
  • Proficient use of AI tools and agentic coding practices

#LI-DH2
What's Roku's approach to hybrid working?
Roku fosters an inclusive and collaborative environment where teams generally work in the office Monday through Thursday. Fridays are generally flexible for remote work, except for employees whose specific roles or assigned office location require five days' a week attendance.
What are some of the benefits?
Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter.
Accommodations
Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to EmployeeRelations@Roku.com.
What should I know about Roku's culture?
Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We're independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV.
We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002.
To learn more about Roku, our global footprint, and how we've grown, visit https://www.weareroku.com/factsheet.
By providing your information, you acknowledge that you want Roku to contact you about job roles, that you have read Roku's Applicant Privacy Notice, and understand that Roku will use your information as described in that notice. If you do not wish to receive any communications from Roku regarding this role or similar roles in the future, you may unsubscribe at any time by emailing WorkforcePrivacy@Roku.com.