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Senior Machine Learning Engineer Jobs in Tennessee

Senior Machine Learning Engineer

Nashville, TN · On-site

$100.90K - $138.60K/yr

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 ...

Senior Machine Learning Engineer

Nashville, TN

$100.90K - $138.60K/yr

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 ...

Senior Machine Learning Engineer

Nashville, TN · On-site

$118.30K - $156K/yr

The Senior Machine Learning Engineer will contribute to both classical machine learning and generative AI applications, collaborating closely with AI Product Managers and a distributed team to build ...

Senior Machine Learning Engineer

Nashville, TN

$100.90K - $138.60K/yr

Role Overview Grailed is looking for a Senior Machine Learning Engineer to drive personalization, recommendation, and product marketplace improvement efforts. This is a high-impact role for an ...

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Showing results 1-20

Senior Machine Learning Engineer information

See Tennessee salary details

$54K

$114.9K

$166.5K

How much do senior machine learning engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for senior machine learning engineer in Tennessee is $114,865.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,800.00 and $130,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Senior Machine Learning Engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for 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 job categories do people searching Senior Machine Learning Engineer jobs in Tennessee look for? The top searched job categories for Senior Machine Learning Engineer jobs in Tennessee are:
What cities in Tennessee are hiring for Senior Machine Learning Engineer jobs? Cities in Tennessee with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer

Senior Machine Learning Engineer

TheIncLab

Nashville, TN • 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.  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.