Machine Learning Computer Vision Engineer

1 week ago

Singapore ST Engineering Full time

Machine Learning Computer Vision Engineer

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.
  • 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 big company resources.
  • International environment where the majority of the team and leadership is from startups or big international corporations 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.
Senioriy level
  • Mid-Senior level
Employment type
  • Contract
Job function
  • Information Technology
Industries
  • Defense and Space Manufacturing
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