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Machine Learning Computer Vision Engineer – End-to-End Vision Systems (2 contract years) - D20 Bishan, Ang Mo Kio, SG

ST ENGINEERING IHQ PTE. LTD.D20 Bishan, Ang Mo Kio, SG

11 days ago

Job description

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

Deploy models with containerized environments (Docker, TorchServe, ONNX Runtime, BentoML) and expose via APIs (REST / gRPC).

Collaborate with engineers to integrate models into larger platforms with reliability at scale.

Automation & Orchestration

Design automated pipelines for data validation, retraining, and deployment (RPA).

Implement workflow orchestration with Airflow, Prefect, or Dagster for scheduled training, monitoring, and failure recovery.

Monitoring & Reliability

Monitor production performance, detect drift, and handle recovery gracefully.

Build alerting and observability with Prometheus, Grafana, or OpenTelemetry.

Collaboration & Tooling

Contribute to MLOps tooling for reproducibility, experiment tracking, and data versioning (MLflow, wandb).

Work with AI Engineers to ensure clean integration with orchestration frameworks.

Must-Have Skills

6+ years of ML or CV engineering, including 3+ years building production-grade vision systems.

Strong knowledge of CV tasks and architectures (classification, detection, segmentation).

Proficient in PyTorch, TorchVision, Albumentations, and modern CV frameworks.

Proven experience training and tuning models on real-world datasets.

Skilled in production deployment (Docker, TorchServe, ONNX Runtime, BentoML, Kubernetes).

Strong software engineering foundation : clean Python, Git workflows, testable architecture.

Experience with ML orchestration tools (Airflow, Prefect, Dagster).

Familiarity with monitoring and alerting systems for ML models.

What We Offer

Small, agile team (5–6 engineers + interns) with autonomy and real ownership.

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

Direct collaboration with top AI researchers and computer vision scientists.

Hybrid work setup : ~2–3 days in office per week.

Tell employers what skills you have

Git

Airflow

Kubernetes

Autonomy

Modeling

Pipelines

Experimentation

Segmentation

Software Engineering

Computer Vision

Reliability

Tuning

PyTorch

Python

Docker

Orchestration

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Machine Learning Engineer • D20 Bishan, Ang Mo Kio, SG