Machine Learning Computer Vision Engineer – End-to-End Vision Systems (2 contract years) - ST ENGINEERING IHQ PTE. LTD.

Roles & Responsibilities

We’re looking for a hands-on ML CV Engineer to lead the development and deployment of robust, production-grade computer vision pipelines. In this role, you’ll own the full lifecycle of CV models - from data curation and preprocessing, through model training and evaluation, to deployment, monitoring, and automated retraining.

You’ll play a critical role in ensuring our vision systems remain accurate, responsive, and scalable under real-world conditions. Your work will directly impact applications involving image classification, object detection, segmentation, and other visual inference tasks.

This is a role for someone who thrives in full-stack ML development, combining deep modeling expertise with disciplined engineering and deployment practices.

Key Responsibilities

End-to-End Vision Systems

• Build computer vision pipelines covering data ingestion, cleaning, augmentation, and preprocessing.
• Train and optimize CV models (classification, detection, segmentation) with PyTorch, TorchVision, and modern frameworks (YOLO, Detectron2, MMDetection, DINO).
• Automate evaluation workflows to benchmark performance and detect drift over time.

Production Deployment & Integration

Automation & Orchestration

Monitoring & Reliability

Collaboration & Tooling

Must-Have Skills

What We Offer

Startup feel with a big company resources : International environment where the majority of the team and leadership is from startups or big international corporations (Lazada, Gojek, IBM) and from various countries.

Low-bureaucracy, high-impact startup environment where your code directly supports next-gen AI deployment.

Experimentation and self-development are in our culture

Knowledge sharing and collaboration

Tell employers what skills you have

Git

Airflow

Kubernetes

Autonomy

Modeling

Pipelines

Experimentation

Segmentation

Software Engineering

Computer Vision

Reliability

Tuning

PyTorch

Python

Docker

Orchestration