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Ml Engineer Jobs in Tennessee (NOW HIRING)

omnia

AI/ML Engineer

Franklin, TN · On-site

$113K - $135K/yr

We are committed to using cutting-edge AI/ML capabilities to improve data quality, automation and overall efficiency across the organization. We are hiring a Senior Software Engineer to take the lead ...

OMNIA Partners LLC

AI/ML Engineer

Franklin, TN · On-site

$113K - $135K/yr

We are committed to using cutting-edge AI/ML capabilities to improve data quality, automation and overall efficiency across the organization. We are hiring a Senior Software Engineer to take the lead ...

Ztek Consulting INC

AI/ML Engineer

Franklin, TN · On-site

AI/ML Engineer Duration:12 months Location: Onsite at Franklin, TN Work Type: Contract - W2 Rate: Pay range offered to a successful candidate will be based on several factors, including the candidate ...

Stackruit Ltd.

Machine Learning Engineer

Nashville, TN · On-site

Be an ML Engineer & Make a Difference in Healthcare (US Remote-First with Nashville Option) Join TailorCare and use machine learning to improve chronic pain treatment! TailorCare is on a mission to ...

Accenture

Google Senior Data Engineer

Nashville, TN · On-site

$94K - $266K/yr

Implement ML pipelines and help establish MLOps processes (monitoring, retraining, deployment). * Support prompt engineering, embeddings, and retrieval-augmented generation (RAG) experimentation.

Accenture

Google Senior Data Engineer

Morristown, TN · On-site

$94K - $266K/yr

Implement ML pipelines and help establish MLOps processes (monitoring, retraining, deployment). * Support prompt engineering, embeddings, and retrieval-augmented generation (RAG) experimentation.

HCA Healthcare

Staff MLOps Engineer

Franklin, TN · On-site

Staff ML Ops Engineer Job Summary and Qualifications Position Summary The Staff MLOps Engineer plays a pivotal role in shaping our MLOps practice within ITG by building and enhancing a scalable ...

HCA Healthcare

Staff MLOps Engineer

Nashville, TN · On-site

Staff ML Ops Engineer Job Summary and Qualifications Position Summary The Staff MLOps Engineer plays a pivotal role in shaping our MLOps practice within ITG by building and enhancing a scalable ...

Pwc

ERP AI Engineer - Manager

Nashville, TN

$99K - $232K/yr

As a Manager, you will lead teams of data scientists and ML engineers, manage client relationships, and translate complex business challenges into AI-driven strategies and solutions. This role offers ...

HCA Healthcare

Staff MLOps Engineer

Murfreesboro, TN · On-site

Staff ML Ops Engineer Job Summary and Qualifications Position Summary The Staff MLOps Engineer plays a pivotal role in shaping our MLOps practice within ITG by building and enhancing a scalable ...

HCA Healthcare

Staff MLOps Engineer

Lebanon, TN · On-site

Staff ML Ops Engineer Job Summary and Qualifications Position Summary The Staff MLOps Engineer plays a pivotal role in shaping our MLOps practice within ITG by building and enhancing a scalable ...

Intellivo

Senior Data Engineer

Memphis, TN · On-site

$95K - $129K/yr

This person will work closely with Data Science, ML Engineering, and Software Engineering teams to ensure reliable, governed, and performant data delivery across the organization. Core ...

Intellivo

Senior Data Engineer

Memphis, TN · On-site

$95K - $129K/yr

This person will work closely with Data Science, ML Engineering, and Software Engineering teams to ensure reliable, governed, and performant data delivery across the organization. Core ...

Intellivo

Senior Data Engineer

Memphis, TN · On-site

$95K - $129K/yr

This person will work closely with Data Science, ML Engineering, and Software Engineering teams to ensure reliable, governed, and performant data delivery across the organization. Core ...

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All JobsMl Engineer JobsMl Engineer Jobs in Tennessee

Ml Engineer information

See Tennessee salary details

$30K

$80.9K

$128.9K

How much do ml engineer jobs pay per year?

As of Aug 17, 2026, the average yearly pay for ml engineer in Tennessee is $80,944.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,400.00 and $98,900.00 per year, depending on experience, location, and employer.

What is an ML engineer?

ML Engineers, or Machine Learning Engineers, are professionals who design, build, and deploy machine learning models into production systems. They bridge the gap between data science and software engineering, ensuring that machine learning solutions are scalable, reliable, and efficient. ML Engineers work with large datasets, develop algorithms, and optimize models for performance. They also collaborate with data scientists, software developers, and business stakeholders to solve real-world problems using artificial intelligence.

What are the key skills and qualifications needed to thrive as an ML engineer?

To thrive as an ML Engineer, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a degree in a related field. Familiarity with programming languages like Python or R, ML frameworks such as TensorFlow or PyTorch, and data processing tools is typically required, with relevant certifications being a plus. Strong problem-solving, critical thinking, and communication skills help you translate complex data insights into actionable solutions and work effectively in teams. These abilities ensure accurate model development, effective deployment, and successful collaboration on data-driven projects.

What are some common challenges ML engineers face when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring models remain accurate over time as data changes (known as data drift), optimizing models for speed and scalability, and integrating models seamlessly with existing software systems. Additionally, maintaining model performance in real-world environments can require continuous monitoring, retraining, and close collaboration with data engineers and DevOps teams. Addressing these challenges typically involves robust testing, using automated pipelines, and staying up-to-date with the latest MLOps best practices.

What is the difference between Ml Engineer vs Data Scientist?

AspectML EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; knowledge of ML frameworksBachelor's or Master's in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDevelops, deploys, and maintains ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, startups, and enterprises deploying ML solutionsResearch institutions, tech firms, and industries relying on data analysis

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

Are machine learning engineers still in demand?

Machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. They typically require skills in programming, data analysis, and frameworks like TensorFlow or PyTorch, and often find opportunities in tech, finance, healthcare, and other sectors investing in AI solutions.

What are the most commonly searched types of Ml Engineer jobs in Tennessee?

The most popular types of Ml Engineer jobs in Tennessee are:

What are popular job titles related to Ml Engineer jobs in Tennessee?

For Ml Engineer jobs in Tennessee, the most frequently searched job titles are:

What job categories do people searching Ml Engineer jobs in Tennessee look for?

The top searched job categories for Ml Engineer jobs in Tennessee are:

Ml Engineer jobs near you
Infographic showing various Ml Engineer job openings in Tennessee as of August 2026, with employment types broken down into 89% Full Time, 5% Part Time, and 6% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $80,944 per year, or $38.9 per hour.

AI/ML Engineer

omnia

Franklin, TN • On-site

$113K - $135K/yr

Full-time

Re-posted 13 days ago

Job description

Job Title 

Senior Software Engineer (Intelligent Data Systems) 

Location 

Franklin, TN 

Candidates must be legally authorized to work in the U.S. without sponsorship, now and in the future.

Open Position Summary – Senior Software Engineer 

OMNIA Partners has become the largest and most experienced purchasing organization for public and private sector markets by delivering unparalleled scale and solutions. Through further organic growth and strategic acquisitions, OMNIA Partners will continue to drive economies of scale to execute more contracts, in more verticals, with transparent, value-driven pricing for our membership of companies. Our success and growth have been unparalleled in this space. OMNIA Partners is at the forefront of leveraging AI and data-driven solutions to enhance business operations and customer insights. We are committed to using cutting-edge AI/ML capabilities to improve data quality, automation and overall efficiency across the organization. 

We are hiring a Senior Software Engineer to take the lead on designing and building the next generation of our data-driven products. In this role, you will bridge the gap between data science concepts and robust software engineering. You will be responsible for taking innovative ideas – often starting as proofs-of-concept – and architecting them into highly scalable, production-grade systems that drive immediate business impact. 

Your primary focus will be building intelligent automation engines that can ingest vast amounts of unstructured data from the outside world, make autonomous decisions about that data using AI/ML and route actionable intelligence to our sales teams and partners. You will work closely with senior leadership to define technical strategy and join a talented team of engineers and architects dedicated to harnessing the power of AI for operational efficiency and growth. 

Position Responsibilities: 

  • System Architecture & Scaling:Lead the architectural design and implementation of complex backend systems, taking early-stage concepts and maturing them into resilient, high-load production environments.
  • Intelligent Data Acquisition:Develop robust strategies and systems for acquiring large volumes of data from diverse, often unstructured external sources, ensuring high data quality and reliability.
  • Applied AI/ML Integration:Design pipelines that integrate practical AI/ML models (such as text classification, NLP or scoring algorithms) to automate complex decision-making processes and enrich incoming data streams.
  • Data Pipeline Engineering:Build high-throughput data pipelines that ingest, validate, process and route data efficiently to downstream applications, data warehouses and third-party ecosystems.
  • Database Strategy:Optimize data storage and retrieval strategies for large-scale datasets across both relational databases and modern data warehouses.
  • Technology Evaluation:Act as a technical leader by staying current with emerging tools in data engineering and applied AI, recommending adoption where it enhances our capabilities. 

Required Education and Skills: 

  • Software Engineering Foundations:5+ years of backend software engineering experience, with a strong track record of building data-intensive applications.
  • Python Proficiency:Expert-level proficiency in Python, with experience using it for both system building and data processing.
  • Handling Unstructured Data:Demonstrated experience building systems that interact with, ingest and structure messy or complex external data sources at scale.
  • Applied Machine Learning:Practical experience integrating Machine Learning into production software workflows. You don't need to be a research scientist, but you must know how to apply standard ML libraries (e.g., scikit-learn, spaCy, or similar) to solve practical problems like classification, entities extraction or scoring.
  • Database Expertise:Strong understanding of data modeling and performance tuning in relational databases and cloud data warehouses (preferably Snowflake).
  • API & Integration:Deep experience designing and consuming complex APIs to connect internal services with third-party data providers.
  • Cloud-Native Mindset:Experience building and deploying applications in cloud environments (AWS, GCP or Azure). 

Preferred Qualifications: 

  • Experience with containerized deployments (Docker/Kubernetes) and modern orchestration tools (e.g., Airflow, Celery).
  • Bachelor’s or master’s degree in computer science or a related technical field. 

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