Senior Machine Learning Engineer

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Monogram Health

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2019

💼 Consulting

🛡️ Insurance

📦 Logistics

Consulting • Insurance • Logistics

Monogram Health is a leading multispecialty provider that delivers in-home, evidence-based care and benefit management for patients with complex, multiple chronic conditions, with a strong focus on chronic kidney disease and related metabolic, cardiovascular, pulmonary, and behavioral health needs. The company coordinates multispecialty clinical teams (nephrology, cardiology, endocrinology, pulmonology, behavioral health, and palliative care), provides 24/7 home-based support including home dialysis and medication management, and partners with payers and physician groups to improve outcomes, reduce hospitalizations, and lower costs.

📋 Description

• 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 supporting operational and clinical objectives • Analyze large datasets to provide insights for strategic planning, risk assessments, and resource allocation • Bridge research and production gaps related to model outputs and explore alternative use cases for existing models • Partner with program owners and data scientists to align models with program goals, KPIs, and operational details • Create and present machine learning solution proposals to program owners to secure buy-in and facilitate implementation • Promote and follow software development, data engineering, and machine learning best practices • Stay current with advancements in machine learning and data science and apply new techniques to improve model performance and reliability • Evaluate efficiency and accuracy, maintain and update deployed models, and troubleshoot deployment issues • Report to the VP, Data Science • Provide technical mentorship to ML Engineers and data teams

🎯 Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field • Minimum of five (5) years of experience in ML Ops or DevOps • Experience scaling AI products and machine learning models • Python for machine learning model development and deployment • SQL, Databricks, and PySpark for data extraction and manipulation • Experience with ML Ops tools and practices, including MLflow, GitHub Actions, Docker, model registries, and Azure ML • Ability to present technical concepts and models effectively to business and executive stakeholders • Proficiency developing code and analyses following good software development practices • Experience packaging and deploying models in production environments, ideally using Azure cloud services • Understanding of model monitoring, data drift detection, and model retraining strategies • Experience with Git, CI/CD pipelines, and test-driven development • Familiarity with cloud computing platforms, preferably Azure • Advanced problem-solving abilities and proactive approach to addressing business challenges through data-driven solutions • Teamwork and collaboration skills for working effectively in cross-functional teams

🏖️ Benefits

• Medical, dental, and vision insurance • Employee assistance program • Employer-paid and voluntary life insurance • Disability insurance • Health and flexible spending accounts • Competitive compensation • 401k with employer match • Financial wellness resources • Paid holidays • Flexible vacation time/PSSL • Paid parental leave • Work life assistance resources • Physical wellness perks • Mental health support • Employee referral program • BenefitHub for employee discounts