Senior ML Platform Architect – Real-Time Decisioning

tailorcare2023; United States; On-site; USD 180,000 - 260,000; Full time

Job summary

TailorCare seeks a Lead ML/AI Engineer to steer the production platform that turns model outputs into real actions. You will own the decisioning, streaming, and release systems, and align with Databricks lakehouse and AWS services. Expect hands-on leadership for high‑risk components.

You will partner with data science, medical economics, and software engineering to ensure auditable, scalable, and compliant solutions across markets.

Qualifications

• Bachelor's degree or equivalent in CS or related field.
• 8+ years in ML engineering, MLOps, or software engineering.
• Production experience with AWS data and ML services and IaC tools.
• Experience with Databricks, PySpark, Delta Lake, MLflow or equivalent.

Responsibilities

• Own the decisioning and feedback layer between score and action.
• Own the engineering implementation, auditability, and reproducibility of production savings calculations.
• Design event‑driven, real‑time integrations between model output and action systems.
• Define per‑model and per‑decision budgets for compute, streaming, and inference.
• Set production standards for ML models, CI/CD, monitoring, and governance.
• Lead architecture for AWS‑Databricks platform including IaC and secure data handling.
• Guide GenAI apps, LLM pipelines, and guardrails for safe patient data usage.
• Collaborate with data science, medical economics, and engineering teams.
• Mentor engineers and data scientists and uphold release discipline.

Skills

ML engineering

MLOps

Python

SQL

Production systems

Education

Bachelor's degree in Computer Science or related

Tools

Databricks

Kinesis

Kafka

Terraform

CloudFormation

CDK

Job description

TailorCare seeks a Lead ML/AI Engineer to steer the production platform that turns model outputs into real actions. You will own the decisioning, streaming, and release systems, and align with Databricks lakehouse and AWS services. Expect hands-on leadership for high‑risk components.

You will partner with data science, medical economics, and software engineering to ensure auditable, scalable, and compliant solutions across markets.