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# Sr Machine Learning Engineer

- **Company:** CVS Health
- **Location:** Irving, TX, United States (Remote available)
- **Experience:** Expert
- **Salary:** $112,923.0 - $185,400.0
- **Contract:** Permanent contract
- **Skills:** HTML, Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Amazon Web Services, Data Analysis, Application Integration Architecture, Confluence, JIRA, Unit Testing, Microsoft Azure, Big Data, C++ (Programming Language), Cascading Style Sheets (CSS), Cloud Computing, Code Review, Computer Engineering, Continuous Integration, Information Engineering, Data Transformation, DevOps, JSON, Python (Programming Language), Machine Learning, Performance Tuning, Scrum Methodology, Software Engineering, Software Systems, SQL Databases, Unstructured Data, Web Services, Extensible Markup Language (XML), Software Organization, Google Cloud, Feature Engineering, Data Ingestion, Apache Spark, Model Validation, Git, Pandas, Kubernetes, Information Technology, Data Lineage, Data Analytics, Feature Selection, Machine Learning Operations, Software Version Control, Docker, Unsupervised Learning, Jenkins, Programming Languages, Microservices
- **Published:** August 20, 2026
- **Apply:** https://www.juju.com/job/00000000go0agq

## About the Role

Master's degree (or foreign equivalent) in Computer Science, Computer Engineering, Information Technology, Engineering, 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; XML, JSON, HTML, CSS, or JavaScript; Agile methodologies or SAFe Software Development Principles; Web Service APIs; Docker or Kubernetes; JIRA, Rally, or Confluence; Data analytics on large data sets in healthcare, business, or retail sector; Machine learning algorithms; Feature engineering, model training, hyperparameter tuning, distributed model training, and supervised and unsupervised learning implementation; Developing and deploying predictive models or ML systems in a cloud environment (GCP, AWS, or Azure); Machine learning operations such as model versioning, model and data lineage, monitoring, model hosting and deployment, scalability, and

## Description

CVS Shared Services Resources LLC, a CVS Health company, is hiring for the following role in Irving, TX: Sr Machine Learning Engineer to Design, develop, and implement machine learning models to solve business problems using structured and unstructured data. Build scalable ML pipelines that automate data ingestion, preprocessing, training, evaluation, and deployment. Develop software applications and tools to integrate ML models into production environments. Collaborate with data scientists and software developers to refine model requirements and translate prototypes into robust software solutions. Write clean, efficient, and well-documented code using programming languages such as Python, Java, or C++. Optimize ML models for performance and accuracy using hyperparameter tuning, feature selection, and model validation techniques. Deploy machine learning models to cloud or on-prem environments using tools like Docker, Kubernetes, and cloud platforms (e.g., AWS, Azure, GCP).
Monitor and maintain model performance in production, implementing model retraining and version control as necessary. Conduct code reviews and adhere to software development best practices including CI/CD, version control, and unit testing. Develop APIs and microservices to serve ML models and support application integration. Perform data analysis and data engineering tasks including cleaning, transformation, and storage using SQL, Spark, or Pandas. Collaborate with cross-functional teams including product managers, analysts, and engineers to identify and prioritize ML use cases. Utilize and contribute to MLOps frameworks to manage the lifecycle of ML models efficiently. Ensure compliance with data privacy and security standards when handling sensitive datasets. Document machine learning systems, workflows, and decisions for internal knowledge sharing and regulatory requirements. Continuously research and evaluate new ML algorithms and technologies to improve model accuracy and
system efficiency. Benchmark different algorithms for scalability and performance under different data and system conditions. Assist in defining the architecture of software systems involving machine learning components. Participate in sprint planning, stand-ups, and other Agile ceremonies to ensure timely and coordinated delivery of ML solutions.

Remote work permitted but must live within commuting distance of designated office location and remain available to report to office as needed and required. Multiple openings.


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