AI Engineer – Computer Vision & Vision-Language Models
Summary
Build and maintain computer-vision models that detect building defects from drone and telephoto imagery, using PyTorch, CUDA, and AWS GPU infrastructure.
Our client is a Singapore-basedAI company that uses computer vision to analyse drone and telephoto imagery of building exteriors, detecting defects such as cracks, spalling and corrosion for building-compliance inspections. Their production environment runs on AWSwith a GPU compute fleet supporting photogrammetry, 3D reconstruction and AImodel training/serving.
What You’ll Do
- Own and modernise the production defect-detection andclassification model stack
- Migrate legacy computer-vision workloads to supportedruntimes and modern serving infrastructure
- Design and run a structured evaluation of managed vs.self-hosted vision-language models (VLMs)
- Operate distributed inference and GPU batch processingpipelines on AWS
- Contribute computer-vision stages to photogrammetry and3D reconstruction pipelines
- Build dataset curation, annotation and evaluationworkflows over large-scale imagery data
- Establish model evaluation benchmarks and versionedground-truth datasets
Core Key Skills
- 2+ years of ML/computer-vision engineering with modelsin production
- 2+ years running training/inference on AWS (EC2 GPUand/or SageMaker)
- Strong PyTorch and CUDA/GPU engineering background
- Recent hands-on experience with vision-language ormultimodal models
- Python and boto3 automation (S3, EC2, SSM, Lambda)
- Model serving experience (e.g. TorchServe, Docker onEC2)
- Comfortable administering both Linux and Windows GPUhosts
- Experience with photogrammetry, 3D reconstruction (e.g.NeRF/Gaussian Splatting) or drone/geospatial imagery is a strong plus
Nice to Have
- GIS/geospatial tooling familiarity
- Experience in building-inspection or similar regulateddomains
- Image restoration/enhancement or thermal imageryanalysis experience