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Reinforcement Learning Engineer Jobs in Tennessee

Senior Machine Learning Engineer

Nashville, TN ยท On-site

$100.90K - $138.60K/yr

Supervised, unsupervised, and reinforcement learning * Neural networks, decision trees, ensemble ... Feature engineering and preprocessing * Data augmentation strategies for training robustness

Senior Machine Learning Engineer

Nashville, TN ยท On-site

$100.90K - $138.60K/yr

Supervised, unsupervised, and reinforcement learning * Neural networks, decision trees, ensemble ... Feature engineering and preprocessing * Data augmentation strategies for training robustness

... engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal ... Reinforcement Learning Company : Deloitte is a business consulting company that offers audit ...

A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning ... Experience with Deep Learning architectures and/or Reinforcement Learning The wage range for this ...

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Showing results 1-20

Reinforcement Learning Engineer information

See Tennessee salary details

$34.5K

$105.2K

$173.8K

How much do reinforcement learning engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for reinforcement learning engineer in Tennessee is $105,161.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,300.00 and $137,500.00 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 Tennessee? For Reinforcement Learning Engineer jobs in Tennessee, the most frequently searched job titles are:
What cities in Tennessee are hiring for Reinforcement Learning Engineer jobs? Cities in Tennessee with the most Reinforcement Learning Engineer job openings:
Infographic showing various Reinforcement Learning Engineer job openings in Tennessee as of May 2026, with employment types broken down into 73% Full Time, and 27% Contract. Highlights an 100% In-person job distribution, with an average salary of $105,161 per year, or $50.6 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

TheIncLab

Nashville, TN โ€ข On-site

$100.90K - $138.60K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago


Job description

The Mission Starts Here

TheIncLab engineers and delivers intelligent digital applications and platforms that revolutionize how our customers and mission-critical teams achieve success.

We are where innovation meets purpose; and where your career can meet purpose as well.โ€ฏ We are looking for a Senior Machine Learning Engineer to that will focus on researching, designing, training, and evaluating machine learning models to solve complex, real-world problems. We encourage you to apply and take the first step in joining our dynamic and impactful company.

Your Mission, Should You Choose to Accept

As a Machine Learning Engineer, you will research, evaluate, and select appropriate machine Learning approaches and architectures based on the problem definition.

What will you do?

  • Research, evaluate, and select appropriate machine learning approaches and architectures based on the problem definition
  • Supervised, unsupervised, and reinforcement learning
  • Neural networks, decision trees, ensemble methods
  • Transformer-based models, adversarial networks, genetic algorithms
  • Retrieval-Augmented Generation (RAG) where appropriate
  • Design and implement machine learning models using frameworks such as PyTorch, TensorFlow, or equivalent
  • Formulate and solve optimization problems using ML techniques
  • Pathfinding and routing
  • Combinatorial and constraint-based optimization Heuristic and learning-based optimization approaches
  • Own data pipelines for ML systems
  • Data validation and quality checks
  • Feature engineering and preprocessing
  • Data augmentation strategies for training robustness
  • Train, tune, and debug models, addressing issues such as overfitting, instability, bias, and performance degradation
  • Define and apply appropriate evaluation metrics, analyze results and iteratively improve model performance
  • For transformer-based systems
  • Optimize context window usage Manage token budgets, chunking strategies, and retrieval mechanisms
  • Balance performance, accuracy, and computational cost
  • Integrate ML models and data pipelines into production systems
  • Make technical decisions and provide architectural guidance for ML systems
  • Document experiments, results, and design decisions using tools such as Git, Jira, and Confluence
  • Mentor junior engineers and guide best practices in ML development Stay current with emerging ML research, tools, and techniques
  • Ability to travel up to 20%

Requirements

Capabilities that will enable your success

  • Bachelorโ€™s degree in Computer Science, Engineering, Applied Mathematics, or a related field
  • 7+ years of professional experience, including significant hands-on machine learning development
  • Strong understanding of machine learning theory and fundamentals
  • Model selection and evaluation
  • Bias/variance tradeoffs
  • Optimization and loss functions
  • Demonstrated experience training and evaluating models using frameworks such as PyTorch or TensorFlow
  • Experience building and maintaining end-to-end ML pipelines
  • Strong programming skills in Python (additional languages are a plus)
  • Experience working with real-world, imperfect datasets
  • Ability to explain model behavior, tradeoffs, and limitations to both technical and non-technical stakeholders
  • Strong grasp of software engineering best practices and system design

Preferred Qualifications

  • Experience with deep learning architectures (CNNs, RNNs, Transformers)
  • Experience applying ML to optimization, planning, or decision-making problems
  • Familiarity with distributed training or large-scale data processing
  • Experience with experiment tracking tools (e.g., MLflow, Weights & Biases)
  • Experience deploying ML models into production (batch or real-time inference) Background in research-driven or R&D-focused engineering environments

Clearance Requirements

Applicants must be a U.S. Citizen and willing and eligible to obtain a U.S. Security Clearance at the Secret or Top-Secret level. Existing clearance is preferred.

Benefits

At TheIncLab we recognize that innovation thrives when employees are provided with ample support and resources. Our benefits packages reflect that:

  • Hybrid and flexible work schedules
  • Professional development programs
  • Training and certification reimbursement e options for Me
  • Extended and floating holiday schedule
  • Paid time off and Paid volunteer time
  • Health and Wellness Benefits includdical, Dental, and Vision insurance along with access to Wellness, Mental Health, and Employee Assistance Programs.
  • 100% Company Paid Benefits that include STD, LTD, and Basic Life insurance.
  • 401(k) Plan Options with employer matching Incentive bonuses for eligible clearances, performance, and employee referrals.
  • A company culture that values your individual strengths, career goals, and contributions to the team

About TheIncLab

Founded in 2015, TheIncLab (โ€œTILโ€) is the first human-centered artificial intelligence (AI+X) lab. We engineer complex, integrated solutions that combine cutting-edge AI technologies with emerging systems-of-systems to solve some of the most difficult challenges in the defense and aerospace industries. Our work spans diverse technological landscapes, from rapid ideation and prototyping to deployment.

At TIL, we foster a culture of relentless optimism. No problem is too hard, no project is too big, and no challenge is too complex to tackle. This is possible due to the positive attitude of our teams. We approach every problem with a โ€œyesโ€ attitude and focus on results. Our motto, โ€œdemo or die,โ€ encompasses the idea that failure is not an option.

We do all of this with a work ethic rooted in kindness and professionalism. The positive attitude of our teams is only possible due to the support TIL provides to each individual.

At TIL, we believe that every challenge is an opportunity for growth and innovation. Our teams are encouraged to think outside the box and come up with creative solutions to complex problems. We understand that the path to success is not always straightforward, but we are committed to persevering and finding a way forward.

Our culture of relentless optimism is not just about having a positive attitude; it is about taking action and making things happen. We believe in the power of collaboration and teamwork, and we know that by working together, we can achieve great things. Our teams are made up of individuals who are passionate about their work and dedicated to making a difference.

Learn more about TheIncLab and our job opportunities at www.theinclab.com.

*Salary range guidance provided is not a guarantee of compensation. Offers of employment may be at a salary range that is outside of this range and will be based on qualifications, experience, and possible contractual requirements.

*This is a direct hire position, and we do not accept resumes from third-party recruiters or agencies.