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Urgent! Machine Learning Computer Vision Engineer – End-to-End Vision Systems (2 contract years) Job Opening In WorkFromHome – Now Hiring ST ENGINEERING IHQ PTE. LTD.

Machine Learning Computer Vision Engineer – End to End Vision Systems (2 contract years)



Job description

Overview

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.

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Required Skill Profession

Electrical & Energy Engineering



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