ML Engineer
Location:

Hybrid
Employment Type:

Full-time

Roles & Responsibilities
Model Development:

Design, build, and deploy machine learning models across classical, time-series, and deep learning approaches to solve real business problems.
Data Pipelines:

Build and maintain reliable data ingestion and transformation pipelines, ensuring data quality, consistency, and reproducibility.
Feature Engineering:

Engineer high-quality features from structured and unstructured data, and manage them through feature stores for training and serving consistency.
Experimentation:

Run rigorous experiments using proper validation strategies, perform hyperparameter tuning, and benchmark models against well-defined baselines.
Model Deployment:

Package models into containerised services, expose them via APIs, and deploy to cloud ML platforms for scalable, low-latency inference.
MLOps & Automation:

Im...