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# Machine Learning Engineer Senior

- **Company:** AmeriHealth Caritas
- **Location:** Newtown Square, PA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Continuous Integration, Data Control, Information Engineering, DevOps, Python (Programming Language), Machine Learning, Standard Sql, Generative AI, Pyspark, Information Technology, Machine Learning Operations, Software Version Control, Databricks
- **Published:** September 11, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3386424603&tx=FL131FFK&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Bachelor's Degree in computer science, engineering, data science, other technical field or extensive relevant experience is required
 * Three to five (3 - 5) years' experience ML engineering, data science or similar experience
 * Fluency in python and SQL
 * Experience in building and operating production ML systems in a Databricks environment (Azure preferred) including PySpark, MLFlow, Feature Stores, and Azure DevOps or comparable technologies
 * Practical knowledge of experiment tracking, reproducible pipelines, model and data monitoring and governance
 * Ability to turn one-off experiments into reliable, reusable capabilities
 * Comfort operating in a cross-functional environment with evolving requirements and shared ownership boundaries across Data Science, Data engineering, DevOps, Platform, Infrastructure, and Security teams
 * Experience in regulated environments, healthcare data, platform engineering is valuable but not required

## Description

* Develop and deploy end-to-end machine learning pipelines on the Azure Databricks platform
 * Collaborate with data scientists, engineers, and stakeholders to understand project requirements and translate them into scalable ML solutions
 * Design and implement systems, infrastructure, and tools for efficient model training, evaluation, and deployment
 * Ensure the scalability, reliability, and security of machine learning systems in production environments
 * Monitor and troubleshoot deployed ML systems, addressing issues related to performance, data quality, and reliability
 * Implement and improve CI/CD processes for machine learning models, enabling seamless updates, version control, automated validation and quality control
 * Stay up to date with the latest advancements in ML and Artificial Intelligence and identify opportunities for innovation and optimization
 * Provide guidance and mentorship on ML across the organization, fostering a culture of continuous learning and growth
 * Help shape emerging GenAI capabilities, including internal evaluation tooling and environments


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