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Junior Machine Learning Jobs in Tennessee (NOW HIRING)

Senior Machine Learning Engineer

Nashville, TN · On-site

$100K - $138K/yr

Mentor junior engineers and guide best practices in ML development Stay current with emerging ML ... Strong understanding of machine learning theory and fundamentals * Model selection and evaluation

Mentor junior engineers and guide best practices in ML development Stay current with emerging ML ... Strong understanding of machine learning theory and fundamentals * Model selection and evaluation

Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing ... Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns ...

Lead AI and Data Science Engineer II

Memphis, TN · On-site

$99K - $131K/yr

Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing ... Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns ...

Lead AI and Data Science Engineer II

Hermitage, TN · On-site

$89K - $118K/yr

Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing ... Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns ...

AI Engineer

Nashville, TN · On-site

$55K - $187K/yr

... junior team members in AI implementation and data engineering practices What You Must Have - At ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

... junior team members and fostering a collaborative work environment What You Must Have - At least a ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

New

Senior Data Scientist

Nashville, TN · On-site

$100K - $209K/yr

Mentor junior data scientists on statistical rigor, modeling best practices, experiment evaluation ... Stay current on advances in statistics, machine learning, and data science; assess and apply ...

The Data Scientist combines strong technical expertise in statistical modeling and machine learning ... In addition to hands-on delivery, this role contributes to team capability by mentoring junior ...

The Data Scientist combines strong technical expertise in statistical modeling and machine learning ... In addition to hands-on delivery, this role contributes to team capability by mentoring junior ...

Work with clients to design, develop, and deploy new architectures to support machine learning ... Mentor, motivate, and coach junior members on technical best practices and inspire professional ...

An ideal environment for recent trade school graduates (e.g., TCAT) or junior machinists looking to ... Continuous Learning: Complete assigned technical, administrative, and hands-on training programs to ...

An ideal environment for recent trade school graduates (e.g., TCAT) or junior machinists looking to ... Continuous Learning: Complete assigned technical, administrative, and hands-on training programs to ...

An ideal environment for recent trade school graduates (e.g., TCAT) or junior machinists looking to ... Continuous Learning: Complete assigned technical, administrative, and hands-on training programs to ...

An ideal environment for recent trade school graduates (e.g., TCAT) or junior machinists looking to ... Continuous Learning: Complete assigned technical, administrative, and hands-on training programs to ...

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Showing results 1-20

Junior Machine Learning information

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

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What does a junior machine learning engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What types of projects and tasks can a junior machine learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer?

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.
What are the most commonly searched types of Machine Learning jobs in Tennessee? The most popular types of Machine Learning jobs in Tennessee are:
What are popular job titles related to Junior Machine Learning jobs in Tennessee? For Junior Machine Learning jobs in Tennessee, the most frequently searched job titles are:
Infographic showing various Junior Machine Learning job openings in Tennessee as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Machine Learning Engineer

TheIncLab

Nashville, TN • On-site

$100K - $138K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 18 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 includes, Dental, and Vision insurance along with access to Wellness, Mental Health, and Employee Assistance Programs.
  • Supplemental Life Insurance options for employees and family members.
  • 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.