Machine Learning Engineer Sr

Amerihealth Caritas•,

7d•Remote

About The Position

We are seeking a hands-on Senior Machine Learning (ML) Engineer to help build out a scalable approach to development, evaluation, deployment, and monitoring of ML models serving millions of members. Our ML Engineering team supports data science teams by helping implement best practices for development and overseeing deployment and continuous operations of ML processes in production within Azure Databricks platform.

Requirements

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

Nice To Haves

Experience in regulated environments, healthcare data, platform engineering is valuable but not required

Responsibilities

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