Machine Learning Computer Vision Engineer – End-to-End Vision Systems

4 weeks ago

Singapur, Singapore ST ENGINEERING IHQ PTE. LTD. Full time

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. #J-18808-Ljbffr

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