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Machine Learning Engineer Jobs in Tennessee (NOW HIRING)

Senior Machine Learning Engineer

Nashville, TN · On-site

$100K - $138K/yr

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 ...

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 ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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Showing results 1-20

Machine Learning Engineer information

See Tennessee salary details

$28.6K

$116.9K

$175.6K

How much do machine learning engineer jobs pay per year?

As of Jul 8, 2026, the average yearly pay for machine learning engineer in Tennessee is $116,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,100.00 and $140,700.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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 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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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.

What are the most commonly searched types of Machine Learning Engineer jobs in Tennessee? The most popular types of Machine Learning Engineer jobs in Tennessee are:
What cities in Tennessee are hiring for Machine Learning Engineer jobs? Cities in Tennessee with the most Machine Learning Engineer job openings:
What are popular job titles related to Machine Learning Engineer jobs in TN? For Machine Learning Engineer jobs in TN, the most frequently searched job titles are:
Infographic showing various Machine Learning Engineer job openings in Tennessee as of July 2026, with employment types broken down into 93% Full Time, 2% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $116,873 per year, or $56.2 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

TheIncLab

Nashville, TN • On-site

$100K - $138K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 17 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.  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

  • Bachelor’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 (“TIL”) 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 “yes” attitude and focus on results. Our motto, “demo or die,” 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.