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Machine Learning Operations Jobs in Tennessee (NOW HIRING)

LP Building Solutions

Data Scientist

Nashville, TN · On-site

... machine learning, you will partner with the business to uncover opportunities, optimize performance, and drive data-informed outcomes. This role will partner closely with marketing, sales, operations ...

Domtar

Sr Process Engineer - Paper Machine

Kingsport, TN · On-site

$99K - $128K/yr

Through our focus on safety and sustainability, as well as our commitment to operational excellence ... Willing to explore machine learning principles * Safety * Be a safety advocate, lead by example

Domtar

Sr Process Engineer - Paper Machine

Kingsport, TN

$99K - $128K/yr

Through our focus on safety and sustainability, as well as our commitment to operational excellence ... Willing to explore machine learning principles * Safety * Be a safety advocate, lead by example

SpaceXAI

Manager, Site Operations

Memphis, TN

As the Site Operations Manager, you'll oversee the data center technicians who keep SpaceXAI's AI ... Experience supporting compute-heavy environments like AI, machine learning, or high-performance ...

Prophecy Technologies

Senior Data Engineer

Memphis, TN · On-site

$103K - $139K/yr

Knowledge of machine learning models and data science techniques in a healthcare setting. * Experience working with FHIR, HL7, and other healthcare data standards . * Familiarity with DevOps and CI ...

PNC Bank

$137K - $186K/yr

Partner with business stakeholders to identify opportunities where AI and machine learning can improve customer experience, operational efficiency, and decision-making. Leadership & Stakeholder ...

SpaceXAI

Site Operations Manager

Memphis, TN · On-site

Preferred : • Experience supporting compute-heavy environments like AI, machine learning, or high ... operations, and advancing sustainability initiatives. • Enthusiasm for xAI's mission to ...

Whiterabbit.ai

Large scale machine learning experience working with terabytes of data * Implemented custom operations/modules in a deep learning framework * Imagination, ambition, and curiosity

Whiterabbit.ai

Large scale machine learning experience working with terabytes of data * Implemented custom operations/modules in a deep learning framework * Imagination, ambition, and curiosity

Whiterabbit.ai

Large scale machine learning experience working with terabytes of data * Implemented custom operations/modules in a deep learning framework * Imagination, ambition, and curiosity

Whiterabbit.ai

Large scale machine learning experience working with terabytes of data * Implemented custom operations/modules in a deep learning framework * Imagination, ambition, and curiosity

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Showing results 41-60

All JobsMachine Learning Operations JobsMachine Learning Operations Jobs in Tennessee

Machine Learning Operations information

What are machine learning operations?

Machine Learning Operations (MLOps) is a set of practices that combines machine learning, software engineering, and DevOps to deploy, monitor, and maintain machine learning models in production environments. It involves tasks such as model versioning, automation, testing, and ensuring scalability and reliability using tools like CI/CD pipelines and cloud platforms.

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

AspectMachine Learning OperationsData Scientist
Primary FocusDeploying, maintaining, and scaling ML models in productionAnalyzing data to develop insights and build models
Required SkillsML deployment, cloud platforms, automation, scriptingStatistical analysis, data visualization, programming (Python/R)
Work EnvironmentOperations teams, cloud infrastructure, production systemsResearch environments, data analysis teams, R&D
Common CertificationsCloud certifications, MLOps tools certificationsData science certifications, statistical courses

Machine Learning Operations and Data Scientists often collaborate, but MLOps focuses on deploying and maintaining models in production, while Data Scientists focus on analyzing data and developing models. Both roles require technical skills, but their day-to-day tasks and environments differ.

Is machine learning operations a high paying job?

Machine Learning Operations (MLOps) roles typically offer high salaries due to the specialized skills required, such as expertise in cloud platforms, automation, and data engineering. Compensation varies based on experience, location, and company size, but generally ranks above average compared to other tech roles.
Machine Learning Operations jobs near you
Infographic showing various Machine Learning Operations job openings in Tennessee as of August 2026, with employment types broken down into 84% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution.

Data Scientist

LP Building Solutions

Nashville, TN • On-site

Full-time

Re-posted 21 hours ago

Job description

Data Scientist
Req Id: 12517
Job Location: Home Office LP, Nashville
Posting Start Date: 6/4/26
Work Environment: Hybrid
Job Description:
Job Purpose
LP Building Solutions, a large specialty building products manufacturer, is looking for a full-time data scientist to join the data analytics team. Leveraging advanced analytical techniques, statistical modeling, and/or machine learning, you will partner with the business to uncover opportunities, optimize performance, and drive data-informed outcomes. This role will partner closely with marketing, sales, operations, supply chain, corporate, and finance teams to identify opportunities, develop predictive and prescriptive models, and deliver actionable insights that improve revenue growth, operational efficiency, and margin performance. This role combines advanced data science techniques with business partnership to identify opportunities, solve complex problems, and generate insights for decision support.
The ideal candidate combines strong technical expertise in statistical modeling and advanced analytics with the ability to translate complex data into clear, business-relevant insights for marketing and sales teams. This individual will work with large, complex datasets spanning manufacturing, distribution, pricing, and customer behavior. This role requires a strong blend of analytical rigor and business acumen, with the ability to work cross-functionally and influence stakeholders. While this role does not require hands-on data engineering responsibilities, it demands close collaboration with the Data Engineering team. Candidates should have a solid understanding of core data engineering concepts to effectively partner, translate business needs, and ensure alignment across data workflows and infrastructure.
In this position you will have the opportunity to:
  • Complete end-to-end data science initiatives, from business problem framing and data exploration through model development, validation, deployment partnership, and performance monitoring.
  • Work directly with internal and external customers to define success criteria, hypotheses, and measurable outcomes. Translate the business needs into analytics/reporting requirements to support executive decisions and workflows with required information.
  • Design, build, and evaluate predictive, prescriptive, and statistical models that improve decision-making, operational efficiency, customer outcomes, or financial performance
  • Design and evaluate experiments to test hypotheses, measure impact, and guide decisions (e.g., A/B, Multivariate, simulation, scenario, Quasi, etc.)
  • Apply advanced analytical methods such as machine learning, forecasting, optimization, causal inference, and experimentation to solve high-value business problems.
  • Proactively identify trends and patterns and generates insights for business units and senior leadership
  • Work with the IT Data Engineering team to integrate data from multiple sources including CRM, ERP, Operational systems, web analytics, and third-party datasets for analysis
  • Research and implement cutting-edge techniques and tools in machine learning/artificial intelligence to make data analysis more efficient
  • Present insights and recommendations to stakeholders in a clear, business-focused manner. You will need to simplify complex methodologies into actionable business insights
  • Establish processes and tools that monitor, analyze and continuously improve model performance and data accuracy
  • Partner with the Analytics leadership team to align initiatives and strategy. Contribute to enterprise analytics roadmap and best practices.
  • Support other Analytics team members by providing technical guidance, peer review, and thought partnership.

What do I need to be successful?
  • 5+ years of progressive experience supporting marketing and sales teams in data science, advanced analytics, or a closely related field
  • Experience in the development of Machine Learning models and AI frameworks
  • Experience working with data visualization and business intelligence tools to communicate insights effectively. (e.g., Tableau, Power BI, or similar tools)
  • Experience working with enterprise data platforms (e.g., Snowflake, Databricks, Cloudera, BigQuery)
  • Experience working with data from large enterprise applications (e.g., ERP, CRM or Operational systems)
  • Preferred experience working with SAP (S/4 HANA, ECC, BTP, etc.)
  • Preferred experience working with Cloud platforms (AWS, Azure, or GCP)
  • Preferred experience in text analytics, image recognition, graph analysis, or other specialized ML techniques, such as deep learning
  • Preferred experience in manufacturing, building products, or construction-related industries.
  • Fluency in multiple analytical programming languages such as Python & SQL (required), R (optional)
  • Demonstrated experience developing and validating statistical models, machine learning algorithms, and advanced analytical solutions using large, complex datasets.
  • Strong competency in Statistical & Quantitative Methods (e.g., Hypothesis testing, regression, probability theory, experimental design etc)
  • Demonstrated experience and comfortable with experimentation and causal analysis.
  • Demonstrated experience with experimental design, model evaluation, and performance measurement.
  • Strong understanding of data pipelines, ETL processes, and data architecture
  • Proven success in supervised and unsupervised learning (e.g., regression, classification, clustering)
  • Strong understanding of AI, its potential roles in solving business problems, and the future trajectory of generative AI models
  • Excellent presentation, communication and stakeholder management skills, with the ability to explain technical concepts in business terms to a diverse audience with a wide range of understanding
  • Highly self-motivated with proven ability to operate autonomously. managing multiple priorities, in a fast-paced environment
  • Willingness and ability to learn new technologies on the job with a continuous learning and innovation mindset

Education
  • Bachelor's degree in computer science, mathematics, data science, statistics, or a related quantitative field.
  • Master's degree preferred.

Work Environment
  • This position may be remote, working in a home office environment, but Nashville, TN candidates are strongly preferred.
  • Occasional travel up to 15% of time.
  • Occasional exposure to a plant environment.

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