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Reinforcement Learning Engineer Jobs in Alabama (NOW HIRING)

Leidos

Senior AI Security Researcher

Huntsville, AL · On-site

$112.80K - $154.70K/yr

This role works alongside junior and senior engineers and research scientists with expertise in ... Experience with adversarial machine learning, reinforcement learning, or multi-agent systems ...

Leidos

Senior AI Security Researcher

Huntsville, AL

$112.80K - $154.70K/yr

This role works alongside junior and senior engineers and research scientists withexpertisein ... Experience with adversarial machine learning, reinforcement learning, or multi-agent systems ...

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Reinforcement Learning Engineer information

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$34.4K

$105K

$173.6K

How much do reinforcement learning engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for reinforcement learning engineer in Alabama is $105,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,200.00 and $137,300.00 per year, depending on experience, location, and employer.

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 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 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 Alabama? For Reinforcement Learning Engineer jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Alabama look for? The top searched job categories for Reinforcement Learning Engineer jobs in Alabama are:
What cities in Alabama are hiring for Reinforcement Learning Engineer jobs? Cities in Alabama with the most Reinforcement Learning Engineer job openings:
Reinforcement Learning Engineer jobs near you
Senior Machine Learning Engineer | AI/ML Maestro

Senior Machine Learning Engineer | AI/ML Maestro

Infinity Labs LLC

Huntsville, AL • On-site

$103.60K - $142.30K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago

Job description

Job Title: Machine Learning Engineer | AI/ML Maestro
Location: Huntsville, AL
This position is open for a Senior AI/ML Engineer specializing in reinforcement learning (RL) and defense-related modeling and simulation. Candidates must meet the general requirements below to be considered. Additional qualifications for senior-level applicants are listed throughout the description.
Who You Are:
You wield artificial intelligence like a six-shooter, deploying machine learning algorithms with the precision of a marksman. You're a problem solver who doesn't flinch at complex military simulations, integrating AI with DoD frameworks to provide decision-makers with real-time insights. With a sharp mind for AI/ML and a deep understanding of simulation environments, you thrive in secure, high-stakes settings. You don't just consume research-you apply it, innovate on it, and deploy it in real-world scenarios that shape national security.
Who We Are:
Infinity Labs is an innovation-driven company with world-class expertise in the defense and national security sectors. Infinity provides cutting-edge engineering technologies and solutions, including modeling, simulation, and analysis (MS&A), research and development (R&D), cyber operational technology, and training. Our extensive project portfolio covers a vast range of physical scales and applications, from materials and components to subsystems, platforms, and systems of systems. We integrate science and systems as part of our overall solutioning approach and we investigate advanced concepts and technologies with disruptive application potential. The sophistication of our work directly reflects the ingenuity and proficiency of our team. Our workforce shapes the future, and our employees are our greatest asset.
What You'll Do:
  • Design, develop, and integrate machine learning models into defense simulations and real-world decision-making systems.
  • Apply a broad range of AI/ML techniques, including supervised learning, unsupervised learning, and deep learning to optimize system performance.
  • Work with large-scale datasets, developing data pipelines and feature engineering processes to support training and inference.
  • Collaborate with DoD civilians, contractors, and stakeholders to align ML solutions with mission objectives.
  • Develop high-performance, scalable AI architectures for deployment on cloud and HPC environments.
  • Optimize machine learning workflows, ensuring computational efficiency and maintainability in resource-constrained settings.
  • Build visualization tools, dashboards, and scripts to analyze model performance and interpret AI-driven insights.
  • Stay ahead of the latest advancements in AI/ML, incorporating cutting-edge research into practical applications.
  • Engage with the DoD modeling and simulation (M&S) community, presenting findings and collaborating on technical solutions.
  • Develop and optimize deep learning architectures, such as transformers, CNNs, and graph-based neural networks, for mission-driven applications.
  • Lead the development of custom ML libraries and toolkits to enhance AI capabilities across multiple projects.
  • Oversee the design of relational and graph-based database schemas to support large-scale AI-driven analytics.

Minimum Qualifications/What You'll Bring:
  • Expertise in machine learning frameworks such as PyTorch, TensorFlow, and JAX.
  • Proficiency with reinforcement learning algorithms (PPO, SAC, DQN).
  • Hands-on experience integrating AI with modeling and simulation tools (AFSIM, MDASim).
  • Strong programming skills in Python and experience with ML libraries like RLlib and Gymnasium.
  • Cloud computing experience with AWS or DoD HPC environments.
  • Version control proficiency (Git, GitLab, GitHub).

Education/Credentials:
  • 10+ years of experience in AI/ML.
  • B.S. in Physics, Engineering, or Computer Science (STEM). Advanced degree preferred.
  • U.S. citizenship is required for consideration, as this job requires U.S. government security clearance
    • Required - Active Secret clearance
    • Highly Desired/Preferred - Active TS/SCI clearance

Nice to Haves:
  • Experience modifying and extending AFSIM framework capabilities.
  • Familiarity with high-level languages such as MATLAB, Simulink, or Julia.
  • Deep understanding of component-based architectures in AI/ML applications.
  • Demonstrated ability to optimize RL training pipelines for computational efficiency.
  • Contributions to published AI/ML research in a defense or security context.

Physical Demands:
  • Must be able to remain in a stationary position and work on a computer for prolonged periods.

This job description provides a high-level review of the responsibilities of the position and is not intended to be a complete list of all responsibilities, duties or skills that may be required for the job. The job description is subject to review and change at any time and other job-related duties or requirements may be assigned as necessary.
What We Offer:
As a nationally recognized Great Place to Work® and Military Times® Best for Vets: 2025 Employer, we prioritize employee well-being and experience, fostering a culture that values dedicated teams and committed individuals. Our premier total compensation package for eligible employees includes:
  • Comprehensive health benefits including medical, dental, and vision coverage.
  • Company-paid disability and life insurance.
  • Generous 401(k) plan with guaranteed company contribution.
  • Paid time-off options including floating holidays, personal time, parental leave, and community service opportunities.
  • Investment in employee growth and development through tuition reimbursement and discounted tuition programs with select colleges.

Infinity Labs is an equal opportunity employer, including disability/vets.

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