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Ai Machine Learning Engineer Jobs in Tennessee (NOW HIRING)

AI/ML Engineer Experience: 6+ Years Location: Franklin, TN - Onsite We are looking for an ... Design, develop, and deploy machine learning and deep learning models * Analyze large datasets to ...

AI Data Engineer - Manager

Nashville, TN

$110.60K - $132.80K/yr

AI Data Engineer - Manager Our Human Capital practice is at the forefront of transforming the ... Lead the development of AI models (e.g., machine learning, natural language processing, computer ...

AI Data Engineer Manager

Nashville, TN

$110.60K - $132.80K/yr

AI Data Engineer Manager Position Summary Our Human Capital practice is at the forefront of ... Lead the development of AI models (e.g., machine learning, natural language processing, computer ...

AI Data Engineer Senior Consultant

Nashville, TN · On-site +1

$102.40K - $139.10K/yr

Deliver governed datasets and feature engineering and serving patterns for machine learning ... AI Data Engineer Senior Consultant Position Summary Our Deloitte Human Capital team transforms ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... Responsibilities - Work with cross-functional teams to incorporate AI into various applications ...

Senior AI Engineer - SFL Scientific

Nashville, TN · On-site

$100.90K - $138.60K/yr

... machine learning applications. Responsibilities : • Work with clients to design, develop, and ... cloud or on prem • Adopt best engineering practices in automation, HPC and AI/GenAI ...

New

We're partnering with forward-thinking companies that are scaling their machine learning operations and real-time AI deployments. As an AI Engineer, you'll play a pivotal role in designing, training ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... AI solutions that enhance product offerings. As a Senior Associate, you will analyze complex ...

AI Engineer Location: Arnold AFB, TN Job Family Code: Digital Enterprise Function/Branch ... Utilize machine learning tools to select features, build, and optimize classifiers that generate ...

AI Engineer Location: Arnold AFB, TN Job Family Code: Digital Enterprise Function/Branch ... Utilize machine learning tools to select features, build, and optimize classifiers that generate ...

AI Engineer

Arnold Air Force Base, TN · On-site

$85K - $115K/yr

AI Engineer Location: Arnold AFB, TN Job Family Code: Digital Enterprise Function/Branch ... Utilize machine learning tools to select features, build, and optimize classifiers that generate ...

AI Engineer Location: Arnold AFB, TN Job Family Code: Digital Enterprise Function/Branch ... Utilize machine learning tools to select features, build, and optimize classifiers that generate ...

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

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Ai Machine Learning Engineer information

See Tennessee salary details

$28.6K

$116.9K

$175.6K

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

As of May 29, 2026, the average yearly pay for ai machine learning engineer in Tennessee is $116,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,100.00 and $140,700.00 per year, depending on experience, location, and employer.

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

To thrive as an AI Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python or R), and a relevant degree such as computer science or engineering. Familiarity with frameworks like TensorFlow, PyTorch, and scikit-learn, as well as experience with cloud platforms and data processing tools, is highly valued, along with certifications in AI or machine learning. Critical thinking, problem-solving, and effective communication are essential soft skills for collaborating with teams and translating business needs into technical solutions. These competencies are crucial for developing accurate, scalable AI models that deliver real-world value and drive innovation.

What are some common challenges that AI Machine Learning Engineers face when deploying models to production environments?

AI Machine Learning Engineers often encounter challenges such as ensuring model scalability, managing data pipeline reliability, and handling model drift once solutions are live. They also need to collaborate closely with DevOps and software engineering teams to integrate models seamlessly into existing systems, while maintaining performance and security. Addressing these challenges requires a strong understanding of both machine learning principles and software deployment best practices.

What is an AI Machine Learning Engineer?

An AI Machine Learning Engineer is a professional who designs, builds, and deploys artificial intelligence and machine learning models to solve real-world problems. They work with large datasets, select appropriate algorithms, and optimize models for accuracy and efficiency. Their role often involves both software engineering and data science skills, and they collaborate with other teams to integrate these models into products or services. AI Machine Learning Engineers are in high demand across industries such as technology, healthcare, finance, and more.

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

AspectAi Machine Learning EngineerData Scientist
CredentialsDegree in CS, AI, or related fields; certifications in ML frameworksDegree in CS, Statistics, or related fields; certifications in data analysis
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, where deploying ML models is keyResearch, business intelligence, analytics across industries

While both roles involve working with data and machine learning, Ai Machine Learning Engineers focus on building and deploying scalable ML models in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core focus and responsibilities.

What are popular job titles related to Ai Machine Learning Engineer jobs in Tennessee? For Ai Machine Learning Engineer jobs in Tennessee, the most frequently searched job titles are:
What cities in Tennessee are hiring for Ai Machine Learning Engineer jobs? Cities in Tennessee with the most Ai Machine Learning Engineer job openings:

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Posted 1 hour ago


Job description

Job Title: AI/ML Engineer
Experience: 6+ Years
Location: Franklin, TN - Onsite

Job Description:
We are looking for an experienced AI/ML Engineer with 10 years of overall IT experience and strong expertise in designing, developing, and deploying machine learning models. The ideal candidate should have hands-on experience in building scalable AI solutions and working with large datasets to drive business insights.

Key Responsibilities:

  • Design, develop, and deploy machine learning and deep learning models
  • Analyze large datasets to extract meaningful insights and improve model performance
  • Build and optimize data pipelines for ML workflows
  • Collaborate with cross-functional teams to understand business requirements and translate them into AI/ML solutions
  • Implement and maintain production-level ML systems
  • Monitor model performance and retrain models as needed
  • Stay updated with the latest advancements in AI/ML technologies

Required Skills:

  • Strong experience in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn
  • Hands-on experience with NLP, Computer Vision, or Predictive Analytics
  • Experience with data preprocessing, feature engineering, and model evaluation
  • Knowledge of cloud platforms (AWS, Azure, or Google Cloud Platform) for ML deployment
  • Experience with SQL and handling large datasets
  • Familiarity with MLOps tools and frameworks

Preferred Qualifications:

  • Experience with Generative AI / LLMs (OpenAI, Hugging Face, etc.)
  • Knowledge of Docker, Kubernetes, and CI/CD pipelines
  • Strong problem-solving and analytical skills
  • Excellent communication and collaboration skills