1

Reinforcement Learning Engineer Jobs in Colorado

AI/ML Engineer II

Lone Tree, CO · On-site

$99K - $136K/yr

The AI/ML Engineer II is a mid-level position for individuals with professional experience in ... Implement and test basic reinforcement learning algorithms and generative models under supervision.

... reinforcement learning, and heuristic approaches • Map system complexity and identify efficiency improvements • Rapidly prototype solutions using AI-assisted development tools • Collaborate ...

Toyon has openings for researchers and developers to solve challenging real-world problems using ... Experience in Reinforcement Learning (RL), Computer Vision, or Natural Language Processing (NLP) is ...

Our team provides superior research, development, and engineering services to the Federal ... Hands-on experience with Deep Reinforcement Learning (DRL) and general AI/ML frameworks. * Agentic ...

next page

Showing results 1-20

Reinforcement Learning Engineer information

See Colorado salary details

$40K

$121.8K

$201.4K

How much do reinforcement learning engineer jobs pay per year?

As of Jun 16, 2026, the average yearly pay for reinforcement learning engineer in Colorado is $121,834.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,300.00 and $159,300.00 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 Colorado? For Reinforcement Learning Engineer jobs in Colorado, the most frequently searched job titles are:
What cities in Colorado are hiring for Reinforcement Learning Engineer jobs? Cities in Colorado with the most Reinforcement Learning Engineer job openings:
AI/ML Engineer II

$99K - $136K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago


Sierra Nevada Corporation rating

8.6

Company rating: 8.6 out of 10

Based on 27 frontline employees who took The Breakroom Quiz

17th of 60 rated aerospace companies


Job description

The AI/ML Engineer II is a mid-level position for individuals with professional experience in designing and implementing machine learning algorithms. In this role, you will independently develop and deploy AI/ML solutions to address complex challenges, such as autonomous systems, predictive maintenance, and computer vision. You will take ownership of specific projects, perform data analysis, and optimize models for performance and scalability. This position requires a combination of technical expertise, problem-solving skills, and the ability to collaborate with multidisciplinary teams to meet mission-critical objectives.The ISR (Intelligence, Surveillance & Reconnaissance), Aviation, and Security (IAS) business area is a leader in ISR and aviation, it is a leading prime manned and unmanned aircraft systems integrator for innovative, high-performance ISR and aviation systems. Its end-to-end Command, Control, Computers, Communications and Intelligence, Surveillance & Reconnaissance (C4ISR) capabilities encompass design, integration, test, certification, ground/flight training and complete logistics support. IAS tailors solutions to customer cost, performance, and schedule requirements and designs to consistently exceed expectations - with an unrivaled record of on time and on (or under) budget deliveries.

Responsibilities:

  • Design, implement, and optimize machine learning models for applications such as object detection, signal processing, predictive analytics, and decision-making systems.
  • Develop and maintain data pipelines for collecting, preprocessing, and managing large-scale datasets. Identify data gaps and propose solutions to improve data quality.
  • Conduct performance testing and validation of AI/ML models using rigorous evaluation metrics. Optimize models for accuracy, efficiency, and scalability.
  • Write and deploy efficient, modular code to integrate AI/ML models into operational systems, ensuring reliability and compatibility with existing platforms.
  • Test AI/ML solutions in simulated environments to evaluate performance under real-world conditions. Contribute to system-level debugging and troubleshooting.
  • Collaborate with hardware engineers, software developers, and systems architects to align AI/ML solutions with mission-critical requirements.
  • Document technical designs, workflows, and testing procedures for internal and external use. Share findings and best practices with team members.
  • Explore and integrate emerging AI/ML frameworks, tools, and methodologies to enhance system capabilities and address new challenges.
  • Train, evaluate, and optimize standard AI models (ANNs, CNNs, RNNs) for supervised and unsupervised tasks.
  • Implement and test basic reinforcement learning algorithms and generative models under supervision.
  • Develop and integrate signal processing and computer vision modules to enhance perception and decision-making capabilities.
  • Conduct simulations and performance profiling of AI/ML models on CPU/GPU architectures, identifying bottlenecks.
  • Execute validation and verification procedures, analyze test results, and support system compliance with safety and reliability standards.

Qualifications You Must Have:

  • Bachelor's degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
  • 2+ years of experience in a related field.
  • Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 6 years of related experience is required.
  • Higher level relevant degree may substitute for experience.
  • Practical experience using machine learning frameworks (e.g., TensorFlow, PyTorch) and applying core AI/ML techniques, including supervised, unsupervised, and introductory reinforcement learning methods.
  • Hands-on experience implementing and evaluating ANNs, CNNs, and RNNs in small-scale or pilot projects. Assisted with deploying machine learning models in production or research environments.
  • Proficiency in programming languages such as Python, C++, C# or Java.
  • Strong understanding of supervised and unsupervised learning techniques.
  • Experience deploying AI/ML solutions in production environments.

Qualifications We Prefer:

  • Master's degree in Artificial Intelligence, Machine Learning, or related field. Experience with reinforcement learning or generative AI models (e.g., GANs, Transformers).
  • Working knowledge of Agile or DevOps practices in software/ML project environments.
  • Hands-on experience with at least one advanced ML technique (e.g., clustering or dimensionality reduction) in coursework or projects.
  • Basic experience with GPU programming (e.g., CUDA basics) or using GPUs for ML model training.
  • Exposure to generative models (e.g., GANs, Transformers) or reinforcement learning frameworks.
  • Experience analyzing and processing diverse datasets to extract insights.
  • Familiarity with requirements gathering and basic deployment of ML systems.
  • Awareness of hardware acceleration tools and edge AI concepts.

Essential Functions:

  • Work extensively on a computer for coding, debugging, and integrating AI/ML systems.
  • Travel occasionally to testing sites, customer locations, or conferences (up to 10-20%).
  • Ability to work in a hybrid environment and manage multiple tasks effectively.

This posting will be open for application for a minimum of 5 days and may be extended based on business needs.

Estimated Starting Salary Range: $108,496.89 - $149,183.22. Compensation varies depending on a wide array of factors, such as candidates' key skills, relevant work experience, and education/training/certifications. The disclosed range estimate may be adjusted for any applicable geographic differential associated with the location at which the position may be filled.

SNC offers a generous benefit package, including medical, dental, and vision plans, 401(k) with 150% match up to 6%, life insurance, 3 weeks paid time off, tuition reimbursement, and more.

IMPORTANT NOTICE:

This position requires the ability to obtain and maintain a Secret U.S. Security Clearance. U.S. Citizenship status is required as this position needs an active U.S. Security Clearance for employment. Non-U.S. citizens may not be eligible to obtain a security clearance. The Department of Defense Consolidated Adjudications Facility (DoD CAF), a federal government agency, handles the adjudicative aspects of the security clearance eligibility process for industry applicants. Adjudicative factors which affect the outcome of the eligibility determination include, but are not limited to, allegiance to the U.S., foreign influence, foreign preference, criminal conduct, security violations and illegal drug use.

Learn more about the background check process for Security Clearances.

SNC is a global leader in aerospace and national security committed to moving the American Dream forward. We're known and respected for our mission and execution focus, agility, and disruptive and rapid innovation. We provide leading edge technologies and transformative solutions that support our nation's most critical security needs. If you are mission-focused, thrive in collaborative environments, and want to make our country stronger with state-of-the-art technologies that safeguard freedom, join our team!

SNC is an Equal Opportunity Employer committed to an environment free of discrimination.Employment decisions are made based on merit without regard to race, color, age, religion, sex, national origin, disability, status as a protected veteran or other characteristics protected by law.


What Sierra Nevada Corporation employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom