Lead ML Systems Engineer - End-to-End Product Impact

Western Digital; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Western Digital is seeking an ML Engineer to own the ML systems for product development defects detection, material modeling with limited data, and active learning selection in an AI-driven environment. You will implement CNN/U‑Net/ViT models, build real-time anomaly detection, and manage data-to-model interfaces, MLflow tracking, and CI/CD for reliable deployments.

Collaboration with data engineers and researchers is essential.

Qualifications

• Bachelor's or Master's degree in AI, ML, CS, or related field.
• 1–3 years hands-on ML engineering experience with end-to-end pipeline ownership.
• Strong Python and PyTorch proficiency; CV basics in CNNs, U-Net, ViT, or anomaly detection.

Responsibilities

• Build, train, evaluate, and maintain CNN/U-Net/ViT models for automated inspection and measurement.
• Develop real-time anomaly detection for sensor and time-series data streams.
• Own implementation of surrogate modeling and active learning pipelines.
• Define feature specifications and validate datasets to ensure model training quality.
• Maintain MLflow tracking, containers, and basic CI/CD contributions.
• Provide code review guidance and document design decisions for production handoff.

Skills

Python

PyTorch

Computer Vision

Surrogate Modeling

Active Learning

Data-to-Model Interface

MLOps

Model Evaluation

Technical Documentation

Education

Bachelor's or Master's degree in AI/ML/CS

Tools

MLflow

Docker

Git

Job description

Western Digital is seeking an ML Engineer to own the ML systems for product development defects detection, material modeling with limited data, and active learning selection in an AI-driven environment. You will implement CNN/U‑Net/ViT models, build real-time anomaly detection, and manage data-to-model interfaces, MLflow tracking, and CI/CD for reliable deployments.

Collaboration with data engineers and researchers is essential.