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# Machine Learning Engineer

- **Company:** CVS Health
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $96,034.0 - $144,200.0
- **Contract:** Permanent contract
- **Skills:** Testing (Software), Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Data Analysis, Continuous Integration, Data Distribution Service, Relational Databases, DevOps, Python (Programming Language), Machine Learning, MySQL, Node.Js, SAS (Software), Simple Object Access Protocol (SOAP), Software Engineering, SQL Databases, Web Services, Git, Information Technology, Jenkins
- **Published:** June 22, 2026
- **Apply:** https://dejobs.org/x/x/9F63852AA2494639BE479A80A822BB84/job/

## About the Role

Requirements: Master's degree (or foreign equivalent) in Computer Science, Engineering, Machine Learning, Statistics, Mathematics, Analytics, Information Technology, or a related field and two (2) years of experience in the job offered or related occupation. Requires two (2) years of experience in each of the following:

 * CI/CD, Jenkins, GIT, or DevOps;

 * Java, Python, or Node.js;

 * JavaScript;

 * Agile methodologies or SAFe Software Development Principles;

 * REST, SOAP or Webservice APIs;

 * MySQL;

 * SAS or SQL programming;

 * Software development life cycle (SDLC) and best practices;

 * Software testing, quality assurance, and troubleshooting;

 * Writing application code and deploying to production; and

 * Relational database concepts.

## Description

Position Summary: Aetna Resources, LLC., a CVS Health company, is hiring for the following role in Irving, TX: Machine Learning Engineer to build, deploy, and monitor artificial intelligence (AI)/machine learning (ML) models to automate processes and transform data into meaningful information. Duties include: apply data modeling, machine learning, predictive modeling, and statistical analysis to extract and analyze information and build end-to-end solutions to meet organizational objectives; research, experiment with, implement, train, and re-train ML algorithms and tools; engage with business stakeholders to translate requirements into technical solutions leveraging ML models and technologies; analyze data and identify differences in data distribution that could impact model performance in real-world use cases using industry leading tools, technologies and best practices; design ML approach, apply appropriate techniques, and develop custom algorithms as needed to address business problems
and predict outcomes of interest; apply sampling techniques and investigate adversarial trends, identify behavior patterns, and respond with logic changes; compare models using statistical performance metrics and ensure accuracy of business metrics; visualize, interpret, and report data findings to internal clients and leadership; and collaborate with Data Engineers, Data Scientists, and Product Managers to drive towards business objectives and key performance indicators (KPIs). Telecommuting available. Multiple positions.


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