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Premise Health

Associate Machine Learning Engineer

Premise Health · Brentwood, TN

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  • Hybrid
  • Full-time
  • $76,800 / year
  • Brentwood, TN

Job highlights

  • Deploy ML models and build ML pipelines.
  • Support RAG and agentic AI workflows.
  • Ensure reliable Databricks and cloud infrastructure.
  • Collaborate with data scientists and IT teams.
  • Write production-grade Python and SQL code.

About the role

Associate Machine Learning Engineer

Premise Health is Different on Purpose. Premise Health serves large organizations and their people with exceptional healthcare, resulting in better experiences, better health, and better value, all while helping organizations lower their healthcare costs. Premise's mission is to help people get, stay, and be well. Come join us and see for yourself why amazing health starts with amazing healthcare. For more information, visit www.jobs.premisehealth.com.

The Associate Machine Learning Engineer serves as the engineering and deployment backbone for the team's ML and applied AI initiatives. This role takes models and AI solutions from development to production—deploying predictive models, building ML pipelines, supporting applied AI systems such as RAG pipelines and agentic workflows, and ensuring reliable infrastructure in Databricks and cloud environments.

This is a full time, remote Associate Machine Learning Engineer role.

What You'll Do

MLOps & Applied AI Engineering

  • Deploy and manage predictive models and ML pipelines in Databricks using MLflow
  • Build and maintain CI/CD pipelines for model training, validation, and deployment
  • Configure and manage model serving endpoints for production inference
  • Monitor model performance, data drift, and system health in production
  • Build and support RAG pipelines including vector search, document processing, and retrieval infrastructure
  • Develop and maintain agentic AI workflows and multi-step automation systems
  • Integrate LLM APIs and model serving endpoints into production applications

Collaboration & Communication

  • Work with data scientists to translate model requirements into deployment plans
  • Collaborate with IT and platform teams on infrastructure, security, and access
  • Document deployment processes, architecture decisions, and operational runbooks

Technical Execution

  • Write clean, production-grade Python following software engineering best practices
  • Work with SQL and PySpark for data processing and transformation at scale
  • Build and maintain data pipelines that feed ML models and AI systems
  • Troubleshoot and resolve issues in production ML and AI systems

What You'll Bring

  • Bachelor’s or Master’s degree in Data Science, Applied AI, Computer Science, Software Engineering, or related STEM field; or completion of an accredited data science, applied AI or ML engineering program
  • 0–2 years in data science, ML engineering, MLOps, or applied AI engineering
  • Coursework or projects involving model deployment, ML pipelines, or production ML systems
  • Coursework or projects involving generative AI, LLMs, or agentic AI systems
  • Experience with Python and SQL
  • Understanding of ML algorithms, neural networks, and deep learning concepts
  • Familiarity with MLOps concepts: model serving, experiment tracking, CI/CD for ML
  • Exposure to RAG architectures, vector databases, and LLM integration patterns
  • Exposure to agentic AI concepts and frameworks (e.g., LangChain, LangGraph, etc.)
  • Familiarity with Git and collaborative development workflows
  • Strong problem-solving skills and engineering mindset
  • Healthcare data experience preferred
  • Experience with the following is a plus: Cloud: Azure, Databricks; MLOps: MLflow, Databricks Model Serving, CI/CD pipelines; Applied AI: LangChain/LangGraph, vector databases, Streamlit; Version Control: GitLab; IDE: VS Code
Work-life balance is at the foundation of how decisions are made and where Premise is headed. We can only help people get, stay, and be well if we do the same for ourselves. In addition to competitive pay, Premise offers full-time team members benefits including medical, dental, vision, life and disability insurance, a 401(k) program with company match, paid holidays and vacation time, a company-sponsored wellness program, EAP, access to virtual primary care and virtual behavioral health at no cost for team members and their dependents. Additional benefits can be viewed here: https://jobs.premisehealth.com/benefits.

Premise is an equal opportunity employer; we value inclusion and do not discriminate based on race, color, religion, creed, national origin or ancestry, ethnicity, sex (including pregnancy and related conditions), gender identity or expression, sexual orientation, age, physical or mental disability, genetic information, past, current or prospective service in the uniformed services, or any other characteristic protected under applicable federal, state, or local law.

Premise provides its reasonable and genuinely expected range of compensation for this job of $60,000.00 - $76,800.00 annually. A number of factors will influence the rate offered for this position, including your experience, qualifications, geographic location, and other factors.

For individuals living in Washington or Colorado: Premise offers the following paid time off benefits. Employees will earn 0.0692 hours of paid time off per actual hours worked or based on standard schedule, per pay period, and will receive 10 paid holidays or an equivalent bank of hours aligned to schedule throughout the calendar year. Paid sick leave is satisfied by the paid time off accrual, detailed above.

This posting is anticipated to close within 90 days of 03/27/2026.

Should you have questions regarding this job posting, please contact askhr@premisehealth.com.

Key skills/competency

  • Machine Learning Engineer
  • MLOps
  • Applied AI
  • Databricks
  • Python
  • SQL
  • CI/CD
  • RAG Pipelines
  • Agentic Workflows
  • Cloud Environments

Skills & topics

  • Machine Learning Engineer
  • MLOps
  • Applied AI
  • Databricks
  • Python
  • SQL
  • CI/CD
  • RAG Pipelines
  • Agentic Workflows
  • Cloud
  • Azure
  • MLflow
  • LangChain
  • Data Science
  • Software Engineering
  • Remote Jobs

How to get hired

  • Tailor your resume: Highlight coursework, projects, and any experience with model deployment, ML pipelines, RAG, or agentic AI systems using keywords from the job description.
  • Showcase technical skills: Emphasize your Python, SQL, and understanding of ML algorithms, neural networks, and deep learning. Mention familiarity with MLOps concepts and LLM integration patterns.
  • Demonstrate problem-solving: Provide examples of troubleshooting and resolving issues in production ML or AI systems, and showcase your engineering mindset.
  • Prepare for technical questions: Be ready to discuss your experience with Python, SQL, ML concepts, and MLOps tools like MLflow or CI/CD pipelines.
  • Highlight collaborative experience: Mention any experience working with data scientists or IT teams to translate requirements and document processes.

Technical preparation

Practice Python for ML and data manipulation.,Build small RAG and agentic AI projects.,Familiarize with Databricks and MLflow.,Set up a basic CI/CD pipeline for models.

Behavioral questions

Describe a challenging ML deployment problem.,How do you collaborate with data scientists?,Explain your approach to system monitoring.,Detail your experience with production code.

Frequently asked questions

What are the primary responsibilities of an Associate Machine Learning Engineer at Premise Health?
The Associate Machine Learning Engineer at Premise Health is responsible for the engineering and deployment of ML and applied AI initiatives. This includes deploying predictive models, building ML pipelines, supporting RAG and agentic AI systems, and ensuring reliable infrastructure in Databricks and cloud environments.
What technical skills are most important for this Associate Machine Learning Engineer role?
Key technical skills for this role include proficiency in Python and SQL, understanding of ML algorithms and deep learning concepts, familiarity with MLOps practices (model serving, experiment tracking, CI/CD), and exposure to RAG architectures and LLM integration patterns. Experience with Databricks and cloud environments is also highly valued.
Is this Associate Machine Learning Engineer position remote?
Yes, this is a full-time, remote Associate Machine Learning Engineer position at Premise Health.
What kind of projects can I expect to work on as an Associate Machine Learning Engineer at Premise Health?
You can expect to deploy and manage predictive models and ML pipelines using tools like MLflow within Databricks, build CI/CD pipelines for ML models, develop RAG pipelines with vector search, and create agentic AI workflows. You'll also integrate LLM APIs into production applications.
What is the required educational background for the Associate Machine Learning Engineer position?
A Bachelor's or Master's degree in Data Science, Applied AI, Computer Science, Software Engineering, or a related STEM field is required. Alternatively, completion of an accredited data science, applied AI, or ML engineering program is accepted. Coursework or projects in relevant areas are also considered.
Does Premise Health offer good benefits for this Associate Machine Learning Engineer role?
Yes, Premise Health offers competitive pay and comprehensive benefits for full-time team members, including medical, dental, vision, life and disability insurance, a 401(k) with company match, paid time off, a wellness program, EAP, and access to virtual primary and behavioral health care at no cost.
What is the experience level required for the Associate Machine Learning Engineer role?
This role requires 0-2 years of experience in data science, ML engineering, MLOps, or applied AI engineering. Coursework or projects involving model deployment, ML pipelines, generative AI, or LLMs can substitute for some experience.
What is the salary range for the Associate Machine Learning Engineer at Premise Health?
The expected salary range for this position is $60,000.00 - $76,800.00 annually, with the final offer influenced by factors such as experience, qualifications, and geographic location.