Medical Guardian · 21 hours ago
Machine Learning Engineer
Philadelphia, PA
Full-time
Hybrid
Entry, Mid Level
2+ years expMedical Guardian is a fast-growing digital health and safety company on a mission to help people live a life without limits. They are seeking a highly capable Machine Learning Engineer to design, build, and operationalize ML models and pipelines that drive intelligent decisioning across the MG ecosystem.
Consumer ElectronicsHealth CareMedical
No H1B
Responsibilities
Model Development & ML Engineering
Build, train, and optimize models for predictions such as churn, fall risk signals, emergency intent classification, and behavioral patterns
Implement NLP, embeddings, and LLM-based workflows for contextual understanding of transcripts, messages, and voice interactions
Develop real-time scoring services integrated with Azure Event Hub, Service Bus, and IOE rule engines
Design reusable, modular components for feature engineering, experimentation, and inference
ML Ops & Deployment
Build automated training, retraining, and evaluation pipelines in Databricks / Azure ML / Python
Develop CI/CD workflows for model deployment using Azure DevOps / GitHub Actions
Create scalable inference endpoints using Azure Functions, Container Apps, or APIM
Implement monitoring for model drift, data quality, and performance degradation
Data Engineering for ML
Work closely with Data Engineering to design robust data pipelines
Build feature stores, feature pipelines, and data transformations optimized for machine learning
Ensure traceability, reproducibility, and well documented data assets
Real-Time Orchestration & Automation
Integrate ML outputs into real-time orchestration flows
Contribute to the IOE decision tree, scoring logic, and step orchestration
Build ML-driven triggers for automated campaigns, safety alerts, and proactive outreach
Collaboration & Strategy
Work with the Director of Data Science to define the ML roadmap for IOE
Partner with Product for personalization, engagement, and predictive feature development
Coordinate with Engineering to deliver API endpoints, event triggers, and user facing functionality
Contribute to documentation, experimentation logs, governance, and compliance
Qualification
Required
2+ years of experience in Machine Learning, AI Engineering, or similar roles
Strong proficiency in Python, ML frameworks (scikit-learn, PyTorch, TensorFlow), and data libraries
Hands-on experience with cloud ML workflows (Azure preferred)
Strong engineering fundamentals: APIs, containers, CI/CD, and distributed systems
Experience building and deploying models into production (batch + real-time)
Understanding of NLP, embeddings, and LLM-based workflows
Candidates must be authorized to work in the United States without current or future need for visa sponsorship
Must have the ability to work from our Philadelphia office on Tuesdays and Wednesdays
Preferred
Experience with Azure ML, Databricks, Delta Lake, Event Hub, Function Apps
Experience integrating ML with automation systems (n8n, Logic Apps, Make.com)
Strong background in data quality, monitoring, and model governance
Experience working with healthcare, IoT, or emergency response data
Knowledge of prompt engineering, vector databases, or agentic AI workflows
Benefits
Health Care Plan (Medical, Dental & Vision)
Paid Time Off (Vacation, Sick Time Off & Holidays)
Company Paid Short Term Disability and Life Insurance
Retirement Plan (401k) with Company Match
Company
Medical Guardian
Medical Guardian provides medical alert devices for seniors and peace of mind for their loved ones.
501-1000 employees
Funding
Current Stage
Late StageTotal Funding
unknownKey Investors
Water Street Healthcare Partners
2021-01-11Private Equity
Leadership Team
Geoff Gross
Founder and CEO
Alex Prough
SVP, Health Services
Recent News
Company data provided by crunchbase