Senior Machine Learning Engineer

Monogram Health

About The Position

The Senior Machine Learning Engineer will be responsible for the independent development and deployment of scalable machine learning models, bridging the gap between research and production, and providing technical mentorship to Machine Learning (ML) Engineers and data teams. This work will contribute to the advancement of Monogram’s data science initiatives. These models will be developed using open-source tools and libraries and may be operationalized as batch or real-time model inference endpoints. The models will utilize a variety of data sources, including healthcare claims, operational data from care management platforms, and EHRs. This position will report to the VP, Data Science.

Requirements

Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field. Master’s degree preferred
Minimum of five (5) years of experience in ML Ops or DevOps.
Experience scaling AI products and machine learning models
Use of Python for machine learning model development and deployment, and using SQL, Databricks & PySpark to extract and manipulate data for data engineering tasks.
Experience with ML Ops tools and practices (e.g., MLflow, GitHub Actions, Docker, model registries, Azure ML).
Proficiency presenting technical concepts and models to business and executive stakeholders effectively.
Proficient in developing code and analyses following good software development practices.
Proficiency in packaging and deploying models in production environments, ideally using Azure cloud services.
Enhanced understanding of model monitoring, data drift detection, and model retraining strategies.
Experience with version control systems (GIT), CI/CD pipelines, and test-driven development.
Familiarity with cloud computing platforms, preferably Azure, for deploying and managing data science solutions.
Evidence of advanced problem-solving abilities and a proactive approach to identifying and addressing business challenges through data-driven solutions.
Demonstrated teamwork and collaboration skills, with the ability to work effectively in cross-functional teams.

Responsibilities

Own and implement end-to-end ML workflows, including model versioning, testing, containerization, automated deployment pipelines (CI/CD), and post-deployment monitoring for performance and data drift.
Independently develop and deploy scalable, robust machine learning models to support Monogram’s operational and clinical objectives.
Conduct data analyses of large datasets to provide insights that aid strategic planning, risk assessments, and resource allocation.
Identify and bridge research and production gaps related to model outputs or explore alternative use cases for existing models to enhance reporting and decision-making processes.
Partner with program owners and data scientists to understand program goals, key performance indicators, and operational details to build and ensure that machine learning models are effectively aligned with program intentions.
Create and present machine learning solution proposals to program owners, aiming to secure buy-in and facilitate the implementation of data-driven solutions.
Identify, promote, and adhere to best practices in software development, data engineering, and machine learning to ensure high-quality and maintainable code.
Remain current with the latest advancements in machine learning and data science, applying new techniques and methodologies to improve model performance and reliability.
Continuously evaluate efficiency. accuracy, maintain and update deployed models, troubleshooting any issues that arise during deployment.