Principal AI/ML Engineer — Computer Vision (Singapore)

Hudson RPO Asia Pacific; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

Hudson RPO Asia Pacific in Singapore is seeking a Principal AI/ML Engineer (Computer Vision) to lead advanced CV and AI/ML work in the GEO, covering research direction, model architecture, experiments, and production-ready implementation.

The role demands deep CV/ML expertise, strong PyTorch/TensorFlow skills, and experience deploying scalable ML systems with robust validation. Collaborative across research, engineering, and product teams in a distributed setup.

Qualifications

• PhD or Master in Computer Science, Computer Vision, ML, AI, Applied Math, EE, Robotics or closely related technical field.
• 8+ years hands-on ML/DL experience with strong CV focus.
• Deep knowledge of PyTorch/TensorFlow and Python development.
• Experience with OpenCV, NumPy, Pandas, scikit-learn and modern Python ML stack.
• Experience with object detection, segmentation, image classification, and model evaluation.
• Experience bringing ML models to production with optimization for inference and latency.
• Experience with REST APIs, Docker, CI/CD, MLOps and model versioning.
• Ability to communicate complex topics to cross-functional stakeholders.

Responsibilities

• Lead advanced CV/AI/ML work within GEO and guide research directions.
• Design model architectures and run experiments to improve quality.
• Ensure production readiness and scalability of CV solutions.
• Collaborate with research, engineering, and product teams across locations.

Skills

Python development

PyTorch

TensorFlow

OpenCV

CNNs/Transformers

MLOps

REST APIs

Agile

Education

PhD or Master in CS/EE/ML

Tools

Docker

CI/CD

NumPy

Pandas

scikit-learn

Job description

Hudson RPO Asia Pacific in Singapore is seeking a Principal AI/ML Engineer (Computer Vision) to lead advanced CV and AI/ML work in the GEO, covering research direction, model architecture, experiments, and production-ready implementation.

The role demands deep CV/ML expertise, strong PyTorch/TensorFlow skills, and experience deploying scalable ML systems with robust validation. Collaborative across research, engineering, and product teams in a distributed setup.