
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.
🕒 August 6
🇺🇸 United States – Remote
💵 $140k - $182k / year
⏰ Full Time
🟠 Senior
🤖 Machine Learning Engineer
👻 Ghost score 33%
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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.
• Independently develop and deploy scalable machine learning models • Bridge research and production gaps • Provide technical mentorship to ML Engineers and data teams • Own and implement end-to-end ML workflows, including model versioning, testing, containerization, CI/CD, and post-deployment monitoring • Conduct data analyses of large datasets for strategic planning, risk assessments, and resource allocation • Identify alternative use cases for existing models to enhance reporting and decision-making • 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 • Promote and adhere to software development, data engineering, and machine learning best practices • Apply current machine learning and data science 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
• 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 • Use of SQL, Databricks & PySpark for data extraction and manipulation • Experience with ML Ops tools and practices, including MLflow, GitHub Actions, Docker, model registries, and Azure ML • Proficiency presenting technical concepts and models to business and executive stakeholders • Proficient in developing code and analyses following good software development practices • Proficiency 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 a proactive approach to addressing business challenges through data-driven solutions • Teamwork and collaboration skills for working effectively in cross-functional teams
• Medical, dental, and vision insurance • Employee assistance program • Employer-paid and voluntary life insurance • Disability insurance • Health and flexible spending accounts • 401k with employer match • Financial wellness resources • 20 PTO days • 7 paid holidays • 1 floating day • Paid parental leave • Work life assistance resources • Physical wellness perks • Mental health support • Employee referral program • BenefitHub for employee discounts • Bonus opportunities
Apply Now🕒 August 6
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