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Mlops Machine Learning Engineer Jobs in Tennessee

TheIncLab

Senior Machine Learning Engineer

Nashville, TN · On-site

$100.90K - $138.60K/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 ...

TheIncLab

Senior Machine Learning Engineer

Nashville, TN · On-site

$100.90K - $138.60K/yr

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 ...

DPR Construction

MLOps Engineer

Nashville, TN

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Machine Learning,Data Science, Data Engineering and Software Engineering. Position Overview ...

Inovalon

Senior Machine Learning Engineer

Nashville, TN · On-site

$118.30K - $156K/yr

The Senior Machine Learning Engineer will contribute to both classical machine learning and generative AI applications, collaborating closely with AI Product Managers and a distributed team to build ...

GOAT Group

Senior Machine Learning Engineer

Nashville, TN

$100.90K - $138.60K/yr

Role Overview Grailed is looking for a Senior Machine Learning Engineer to drive personalization, recommendation, and product marketplace improvement efforts. This is a high-impact role for an ...

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Mlops Machine Learning Engineer information

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

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps Machine Learning Engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What does an MLOps Machine Learning Engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

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

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

What are popular job titles related to Mlops Machine Learning Engineer jobs in Tennessee? For Mlops Machine Learning Engineer jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Mlops Machine Learning Engineer jobs in Tennessee look for? The top searched job categories for Mlops Machine Learning Engineer jobs in Tennessee are:
What cities in Tennessee are hiring for Mlops Machine Learning Engineer jobs? Cities in Tennessee with the most Mlops Machine Learning Engineer job openings:
Mlops Machine Learning Engineer jobs near you
Machine Learning Engineer

Machine Learning Engineer

Upperline Health

Nashville, TN • On-site

Full-time

Posted 13 days ago

Upperline Health rating

3.0

Company rating: 3.0 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

Job description

Position Overview: We are looking for a talented Machine Learning Engineer to help build and maintain machine learning pipelines that support predictive healthcare models. This role is ideal for someone with strong data engineering skills and a passion for applying machine learning to real-world healthcare challenges.
Key Responsibilities:
  • Design and implement data pipelines using SQL and Python from various data sources.
  • Synthesize large medical claims data records into useable data features.
  • Collaborate with Data Scientists to build, refine, and deploy various machine learning models in Python.
  • Learn and apply SAS as needed for dataset generation (prior experience is not required).
  • Ensure data quality, reproducibility, and performance in the pipelines.
  • Contribute to best practices for data governance and model deployment.

Qualifications:
  • 2-5+ YOE as a Machine Learning Engineer or Data Scientist with a focus on engineering data builds.
  • Proficiency in SQL/Snowflake and Python; willingness to learn SAS as needed.
  • Experience building and combining data pipelines and working with large datasets.
  • Basic understanding of healthcare claims data (e.g., Medicare claims) preferred.
  • Familiarity with machine learning workflows (e.g., scikit-learn, pandas, NumPy).
  • Strong problem-solving and communication skills, sharp critical thinking skills.
  • Comfortable with a fast-paced workstream that requires flexibility to work on multiple projects or analyses at the same time.

Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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