1

Founding Machine Learning Engineer Jobs in Nashville, TN

Senior Machine Learning Engineer

Nashville, TN ยท 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 ...

Senior Machine Learning Engineer

Franklin, TN ยท Remote

$118K - $155K/yr

Remote - USA As a Senior Machine Learning Engineer (individual contributor) atRevecore, you will: Use yourexpertisein machine learning, exploratory data analysis, and software engineering to enhance ...

Machine Learning Engineer

Nashville, TN ยท On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

next page

Showing results 1-20

Founding Machine Learning Engineer information

See Nashville, TN salary details

$30.4K

$124.4K

$186.9K

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

As of Aug 27, 2026, the average yearly pay for founding machine learning engineer in Nashville, TN is $124,377.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $149,700.00 per year, depending on experience, location, and employer.

What is a founding machine learning engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.

What are some unique challenges and expectations for a founding machine learning engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

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

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.

Are founding machine learning engineers still in demand?

Founding machine learning engineers remain in high demand as companies seek to develop AI-driven products and services. They often require strong skills in deep learning, data modeling, and proficiency with tools like TensorFlow or PyTorch, with demand driven by growth in AI applications across industries.

How much does a founding machine learning engineer make?

A founding machine learning engineer typically earns between $100,000 and $180,000 annually, depending on experience, location, and company size. Equity and bonuses may also be part of the compensation package, especially in startup environments where they play a significant role in total earnings.

What are popular job titles related to Founding Machine Learning Engineer jobs in Nashville, TN?

For Founding Machine Learning Engineer jobs in Nashville, TN, the most frequently searched job titles are:

Senior Machine Learning Engineer

TheIncLab

Nashville, TN โ€ข On-site

$100K - $138K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-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 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.