Staff ML Engineer - Precision AI & Data Pipelines

Western Digital Corporation; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

WD is seeking an early-career ML engineer to join a focused AI team working on precision product development. You will own real responsibilities from day one, learning from engineers and researchers with world-class backgrounds and contributing to physics-informed AI and product ML systems.

You will track experiments, validate data quality, build CNN-based models, and help package pipelines with Docker and CI/CD. Fresh graduates with ML project experience are encouraged to apply.

Qualifications

• Bachelor's or Master's degree in AI, ML, CS, Electrical Engineering, Applied Mathematics, or related field. AI major or strong research focus preferred.
• Fresh graduate to 1 year; ML project competency is primary criterion; strong final-year project or thesis with ML component; internship preferred.
• Must-have skills include PyTorch, CNN architectures, surrogate modeling, active learning, MLflow, Docker, model evaluation, and fast learning.

Responsibilities

• Experiment Tracking & Evaluation Reporting: manage MLflow experiments, run evaluations, and produce reports.
• Training Data Quality Validation: validate datasets, check feature distributions, verify labels, flag anomalies.
• Deep Learning Model Contribution: build/train CNN-based models for image classification and defect detection.
• ML Pipeline Contribution: containerize models with Docker, assist CI/CD, and support deployment validation.

Skills

PyTorch

CNNArchitecture Basics

Surrogate Modeling Concepts

Active Learning Awareness

MLflow Basics

Docker Basics

Model Evaluation

Learning Mindset

Education

Bachelor's or Master's degree in AI/ML/CS/EE/Applied Mathematics

Job description

WD is seeking an early-career ML engineer to join a focused AI team working on precision product development. You will own real responsibilities from day one, learning from engineers and researchers with world-class backgrounds and contributing to physics-informed AI and product ML systems.

You will track experiments, validate data quality, build CNN-based models, and help package pipelines with Docker and CI/CD. Fresh graduates with ML project experience are encouraged to apply.