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Reinforcement Learning Engineer Jobs in Colorado

Sr. AI Engineer

Lone Tree, CO

$106K - $146K/yr

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading ... Demonstrated experience with reinforcement learning and generative AI models in production or ...

... reinforcement learning systems, and generative AI algorithms, to solve complex problems. Architect ... Work with Project Engineer/Project Manager to identify and manage technical risks, develop ...

AI Engineer III

Lone Tree, CO · On-site

$58.75 - $79/hr

The AI/ML Engineer III is a mid-level technical position that requires advanced expertise in ... reinforcement learning systems, and generative AI algorithms, to solve complex problems.

AI Engineer III

Lone Tree, CO

$58.75 - $79/hr

The AI/ML Engineer III is a mid-level technical position that requires advanced expertise in ... reinforcement learning systems, and generative AI algorithms, to solve complex problems.

Sr. AI Engineer

Highlands Ranch, CO · On-site

$102K - $141K/yr

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading ... Demonstrated experience with reinforcement learning and generative AI models in production or ...

Sr. AI Engineer

Lone Tree, CO · On-site

$106K - $146K/yr

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading ... Demonstrated experience with reinforcement learning and generative AI models in production or ...

A.I. Engineer

Denver, CO · On-site

$70/hr

AI Engineer (Machine Learning / LLMs / Agentic AI) Location: Merrifield, VA (Hybrid or Remote for ... Experience with reinforcement learning techniques. * Experience with speech recognition ...

Varstaff is looking for an AI/ML Engineer III Must be a US Citizen. (paid on a W2) In this role ... Demonstrated mastery of deep learning, reinforcement learning, generative models, and large-scale ...

Cymertek Corporation is seeking a passionate and innovative AI/ML Engineer to join their team and ... reinforcement learning • Familiarity with generative AI models • Experience in edge AI ...

Varstaff is looking for an AI/ML Engineer III Must be a US Citizen. (paid on a W2) In this role ... Demonstrated mastery of deep learning, reinforcement learning, generative models, and large-scale ...

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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 Jul 14, 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 job categories do people searching Reinforcement Learning Engineer jobs in Colorado look for? The top searched job categories for Reinforcement Learning Engineer jobs in Colorado are:
What cities in Colorado are hiring for Reinforcement Learning Engineer jobs? Cities in Colorado with the most Reinforcement Learning Engineer job openings:
Sr. AI Engineer

$106K - $146K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago


Sierra Nevada Corporation rating

8.7

Company rating: 8.7 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

13th of 61 rated aerospace companies


Job description

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading the development of complex AI/ML systems, driving innovation, and mentoring team members to deliver impactful solutions. In this role, you will oversee the design, implementation, and deployment of scalable AI/ML models for mission-critical aerospace and defense applications. You will also act as a technical leader, providing strategic guidance on AI/ML initiatives, ensuring compliance with regulatory standards, and collaborating with stakeholders to meet organizational objectives. This position demands advanced technical expertise and the ability to manage high-impact projects in a fast-paced environment.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:

  • Lead the design and development of advanced machine learning models, including deep neural networks, reinforcement learning systems, and generative AI algorithms, to solve complex problems.
  • Architect scalable AI/ML systems that can integrate seamlessly with existing software and hardware platforms. Provide guidance on theselectionof tools, frameworks, and infrastructure.

  • Collaborate with systems engineers, hardware teams, and data scientists to align AI/ML solutions with mission-specific requirements and constraints.

  • Manage AI/ML projects, including scoping, resource allocation, and timeline management, ensuring that deliverables meet quality and performance expectations.

  • Develop and oversee robust validation and testing frameworks to ensure that AI/ML models meet performance, safety, and compliance standards in real-world scenarios.

  • Mentor junior engineers,providingtechnical guidance and fostering a collaborative, innovative team environment.

  • Stay current with emerging AI/ML technologies and propose innovative solutions to address new and existing challenges in the aerospace and defense domain.

  • Communicate technical concepts, project progress, and outcomes to stakeholders, including leadership and external partners, in a clear and concise manner.

  • Independently train, fine-tune, andoptimizeadvanced AI architectures (including transformers) for complex applications.

  • Apply a broad range of AI/ML techniques (supervised, unsupervised, reinforcement, generative) to solve domain-specific challenges.

  • Lead the development and integration of signal processing, computer vision, and planning algorithms to advance autonomous system functionality.

  • Design and execute large-scale simulations and modeling of AI/ML systems, ensuring scalability, performance, and robustness on CPU/GPU platforms.

  • Lead rigorous validation and verification activities, ensuring deliverables meet performance, safety, and reliability requirements.

Qualifications You Must Have:

  • Bachelor's degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
  • 10+ 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 12 years of related experience is required.
  • Higher level relevant degree may substitute for experience.
  • Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques, including supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic). Demonstrated ability to design and optimize generative AI models (e.g., transformers) and neural networks for complex applications.
  • Extensive experience architecting, deploying, and optimizing AI/ML systems, including ANNs, CNNs, and RNNs, in large-scale or mission-critical environments. Led efforts to improve model performance and reliability in production settings.
  • Strong proficiency in programming languages such as Python, C++, C# or Java, with experience in building scalable AI/ML systems.
  • Demonstrated experience leading teams or projects, including mentoring junior staff.
  • Proven track record of deploying AI/ML models in production environments and optimizing them for real-world use cases.
  • Knowledge of regulatory and cybersecurity requirements for AI/ML systems in aerospace and defense applications.
  • Active Secret US Security Clearance

Qualifications We Prefer:

  • Master's degree + additional years experience, or Ph.D. in Artificial Intelligence, Machine Learning, or a related field.
  • Experience with hardware acceleration technologies (e.g., CUDA, TensorRT) and high-performance computing systems.
  • Background in autonomous systems, robotics, or sensor fusion.
  • Familiarity with Agile/DevOps methodologies for software development.
  • Certifications in AI/ML or related fields, such as AWS Certified Machine Learning Specialty or Google Professional Machine Learning Engineer.
  • Deep understanding and practical application of Agile/DevOps in large-scale AI/ML projects.
  • Demonstrated experience with reinforcement learning and generative AI models in production or research settings.
  • Advanced proficiency in GPU programming, parallel/distributed computing, and optimizing ML workloads for performance.
  • Expertise in designing and implementing complex ML pipelines, including clustering, dimensionality reduction, generative modeling, and reinforcement learning, aligned to mission objectives and HMI systems.
  • Skilled in analyzing massive, multi-source datasets and delivering end-to-end autonomy software solutions, from requirements to deployment and maintenance.
  • Working knowledge of hardware acceleration technologies (CUDA, TensorRT), edge AI deployments, and explainable AI (XAI) methods.
  • Exposure to or interest in quantum computing for ML applications.

Essential Functions:

  • Lead and manage AI/ML projects, including end-to-end development and deployment.
  • Collaborate with cross-functional teams and oversee the integration of AI/ML systems into complex aerospace platforms.
  • Travel occasionally (10-20%) to customer sites, testing facilities, or conferences to support project initiatives.
  • Work in a hybrid office environment, balancing technical leadership with hands-on development work.
  • Ensure compliance with safety, regulatory, and cybersecurity standards for AI/ML systems.

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: $143,487.14 - $197,294.82. 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 annual incentive pay based upon performance that is commensurate with the level of the position.

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:

To conform to U.S. Government international trade regulations, applicant must be a U.S. Citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State or U.S. Department of Commerce.

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.


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