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Machine Learning Engineer Jobs in Cookeville, TN

ATC Automation

Machinist Apprentice

Cookeville, TN · On-site

$15.25 - $19.50/hr

... learning from experienced machinists in a hands-on manufacturing environment. As a Machinist ... machine care activities. * Work collaboratively with machinists, engineers, and fabrication ...

ATC Automation

Machinist Apprentice

Cookeville, TN · On-site

$15.25 - $19.50/hr

... learning from experienced machinists in a hands-on manufacturing environment. As a Machinist ... machine care activities. * Work collaboratively with machinists, engineers, and fabrication ...

ATC Automation

Machinist Apprentice

Cookeville, TN · On-site

$15.25 - $19.50/hr

... learning from experienced machinists in a hands-on manufacturing environment.As a Machinist ... basic machine care activities.Work collaboratively with machinists, engineers, and fabrication ...

Mosaic.tech

Lead Robotics Engineer, Autonomy

Cookeville, TN · On-site

$140 - $210/hr

Our unique model of centralized go-to-market and decentralized engineering allows us to move with ... Robot learning (imitation/RL, VLA models), CUDA/edge deployment, and experience operating in rugged ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Cookeville, TN

Machine Learning Engineer information

See Cookeville, TN salary details

$26.9K

$110K

$165.3K

How much do machine learning engineer jobs pay per year?

As of Aug 31, 2026, the average yearly pay for machine learning engineer in Cookeville, TN is $110,002.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,700.00 and $132,400.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs

What job categories do people searching Machine Learning Engineer jobs in Cookeville, TN look for?

The top searched job categories for Machine Learning Engineer jobs in Cookeville, TN are:

What cities near Cookeville, TN are hiring for Machine Learning Engineer jobs?

Cities near Cookeville, TN with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Cookeville, TN as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 21% Part Time, and 1% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $110,002 per year, or $52.9 per hour.

Artificial Intelligence (AI) Engineer / Developer (Remote)

Statheros

Cookeville, TN • On-site, Remote

Contractor

Re-posted 26 days ago

Job description

About Us
Statheros is a small DEFTECH firm focused on developing cutting-edge AI and autonomy systems for the US Department of Defense. Our team is passionate about building intelligent systems that solve complex problems. We are looking for a talented AI Engineer specializing in Proximal Policy Optimization (PPO) to lead the development of AI-enabled algorithms that automate the operation of air traffic radar systems.
Job Responsibilities
  • Design, implement, and optimize Proximal Policy Optimization (PPO) algorithms for domain-specific use cases.
  • Develop and train reinforcement learning models for real-world applications, focusing on efficiency and scalability.
  • Collaborate with cross-functional teams to integrate PPO models into production systems.
  • Analyze model performance and experiment with hyperparameter tuning to achieve optimal results.
  • Stay up-to-date with the latest research and advancements in reinforcement learning and apply them to enhance existing solutions.
  • Build robust pipelines for training, evaluation, and deployment of RL models.
  • Document workflows, methodologies, and code for reproducibility and knowledge sharing.
Qualifications
  • Educational Background: Bachelor's or Master's degree in Computer Science, Machine Learning, AI, Mathematics, or related fields. Ph.D. is a plus.
  • Experience:
    • 4+ years of professional experience in machine learning, with a focus on reinforcement learning.
    • Demonstrated expertise in implementing and optimizing PPO or similar reinforcement learning algorithms.
    • Hands-on experience with frameworks like TensorFlow, PyTorch, or JAX.
  • Technical Skills:
    • Strong programming skills in Python; familiarity with Rust or other languages is a plus.
    • Proficiency in designing and running RL experiments in simulated or real-world environments.
    • Experience with distributed training systems for reinforcement learning.
    • Solid understanding of policy gradient methods and reinforcement learning theory.
  • Soft Skills:
    • Excellent problem-solving skills and the ability to work in a collaborative, fast-paced environment.
    • Strong communication skills for presenting findings and collaborating with interdisciplinary teams.
Preferred Qualifications
  • Experience in applying PPO to [specific domain, e.g., robotics, gaming, finance, etc.]
  • Familiarity with OpenAI Gym, RLlib, or other RL development environments
  • Knowledge of parallel computing and GPU acceleration for large-scale RL tasks
What We Offer
  • Remote work location.
  • Competitive salary.
  • Flexible work schedule.
  • Opportunities for professional development and research contributions
  • Access to state-of-the-art resources and tools for AI development.
  • The chance to work on groundbreaking projects with a talented and passionate team.
Employment Type: CONTRACTOR

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