Machine Learning Engineer

Senior Machine Learning Engineer

About the role
: Own end‑to‑end machine learning for structured, time‑aligned industrial datasets, from data pipelines to production deployments. Deliver reliable, calibrated ML services with strong observability and rollback.

Responsibilities

• Design and maintain robust ETL/feature pipelines for large structured datasets.

• Train and evaluate classification/regression models; implement calibration and uncertainty.

• Build production ML services with CI/CD, versioned artifacts, monitoring, and drift detection.

• Develop secure, low‑latency deployments in on‑prem/VPC environments using containers.

• Create documentation, diagnostics dashboards, and automated alerts/rollback.

Minimum qualifications

• 4+ years shipping ML systems on tabular data in production.

• Strong Python, SQL, and experience with scikit‑learn/XGBoost/LightGBM or tabular DL.

• Proven CI/CD, containerization, and observability skills for ML services.

• Familiarity with calibration (e.g., ECE), PR/ROC evaluation, and imbalanced data handling.

• Experience with secure deployments (access control, secrets, audit logging).

Nice to have

• Background with industrial/manufacturing or time‑series/quality datasets.

• Experience with experiment design, labeling strategies, and slice‑wise diagnostics.

• Cloud ML experience and migration to on‑prem deployments.

How to apply
: Share a resume and a brief note describing one production ML system you shipped (data → deployment → monitoring), highlighting how you handled calibration, drift, and rollback.