Senior ML Systems Engineer - Vision & Anomaly Detection

WD; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

WD is building the infrastructure behind the AI-driven data economy. You will own ML systems that detect product development defects, model material behavior with limited data, and select the highest-value experiments from an active learning pipeline. Your models will run in product development.

Your decisions will matter immediately. Responsibilities include implementing CNN/U-Net/ViT models for automated inspection, maintaining real-time anomaly detection on sensor data streams, and leading

Qualifications

• Bachelor's or Master's in AI, ML, CS or related field.
• 1–3 years of hands-on ML engineering experience with end-to-end pipeline ownership.
• Strong Python and PyTorch proficiency; solid CV/vision fundamentals.

Responsibilities

• Own ML systems for detection of product defects and active learning experiments.
• Build real-time anomaly detection for sensor/time-series data streams.
• Maintain data-to-model interfaces and ML pipelines; monitor & improve model performance.

Skills

Python

PyTorch

CNN/ViT/U-Net

Anomaly Detection

Active Learning

MLOps

Data Validation

Documentation

Experimentation

Education

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

Tools

Docker

Git

CI/CD

AWS basics

MLflow

Job description

WD is building the infrastructure behind the AI-driven data economy. You will own ML systems that detect product development defects, model material behavior with limited data, and select the highest-value experiments from an active learning pipeline. Your models will run in product development.

Your decisions will matter immediately. Responsibilities include implementing CNN/U-Net/ViT models for automated inspection, maintaining real-time anomaly detection on sensor data streams, and leading