Senior Machine Learning Engineer

🕒 August 6

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 20%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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

• Independently develop and deploy scalable, robust machine learning models • Own and implement end-to-end ML workflows, including model versioning, testing, containerization, CI/CD deployment pipelines, and post-deployment monitoring • Conduct data analyses of large datasets to support strategic planning, risk assessments, and resource allocation • Bridge research and production gaps related to model outputs • Explore alternative use cases for existing models to improve 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 follow best practices in software development, data engineering, and machine learning • 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 • Provide technical mentorship to ML Engineers and data teams • Report to the VP, Data Science • Work with healthcare claims, operational care-management data, and EHR data

🎯 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 • 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 • 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 data-driven business challenges • Teamwork and collaboration skills for effective work 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 employee discounts