Senior Real-Time Health AI Engineer (Remote)

GuruLink; Nashville (TN); Remote; USD 140,000 - 210,000; Full time

Job summary

GuruLink is seeking a Senior ML/AI Engineer to take predictive models from prototype to production on a healthcare-focused platform. You will own deployment, retraining, monitoring, and real-time data paths from model output to care teams, collaborating across data engineering, software engineering, clinical, and operations teams.

The role emphasizes a hybrid AWS/Databricks environment, cost control, and HIPAA-conscious handling of patient data.

Qualifications

• 5+ years in ML engineering, MLOps, or data science with 3+ years in production
• Production experience with Databricks, PySpark, Delta Lake, MLflow
• Production AWS data/ML services and infrastructure-as-code
• Experience with event-driven or streaming systems and contracts
• Strong Python and SQL; experience with scikit-learn, XGBoost, or PyTorch
• CI/CD for ML workloads and monitoring
• Bachelor's degree in CS/engineering or equivalent experience

Responsibilities

• Build the layer between model score and action, including logging
• Design real-time integrations and event pipelines from model output
• Track cost to serve, budgets, and alerts for ML workloads
• Deploy, monitor, and retrain production models with CI/CD and registry
• Develop models on healthcare claims and operational data in production
• Drive AWS and Databricks lakehouse build-out with IaC
• Extend feature store to real-time features as new sources appear
• Own GenAI apps, including LLM pipelines with guardrails and cost controls
• Collaborate with data science and engineering for production practice
• Occasional travel up to ~10% for onsite meetings

Skills

ML engineering

MLOps

Databricks

Python

SQL

AWS

CI/CD for ML

Education

Bachelor's degree in CS/Engineering or related

Tools

Databricks

MLflow

Terraform/CDK/CloudFormation

Kinesis/Kafka

Bedrock or similar

Job description

GuruLink is seeking a Senior ML/AI Engineer to take predictive models from prototype to production on a healthcare-focused platform. You will own deployment, retraining, monitoring, and real-time data paths from model output to care teams, collaborating across data engineering, software engineering, clinical, and operations teams.

The role emphasizes a hybrid AWS/Databricks environment, cost control, and HIPAA-conscious handling of patient data.