The opportunity
About the role
Quantaleap is looking for a hands-on Computer Vision Engineer who can design, train and deploy deep-learning models that power real-time image and video analytics. You will collaborate with product, data and backend teams, so clear, proactive communication is essential.
What you bring
What we are looking for
Key responsibilities • Research and prototype computer-vision algorithms for anomaly detection, object detection, tracking and segmentation. • Create end-to-end image-processing and computer-vision pipelines. • Train, fine-tune and optimise CNN and Transformer models in PyTorch or TensorFlow. • Package and deploy models to cloud or edge environments with Docker and Kubernetes. • Automate pipelines for image and video collection, augmentation and annotation. • Monitor model performance in production and drive continuous improvement. • Document findings and present results to technical and non-technical stakeholders. Must-have skills • 3–5 years building computer-vision solutions in production. • Strong knowledge of computer vision and deep learning, including CNNs and Vision Transformers such as YOLO. • Proficiency with PyTorch or TensorFlow, OpenCV and Python. • Experience deploying models through REST or gRPC APIs, or on-device. • Excellent written and verbal communication. Nice to have • Knowledge of CUDA, TensorRT or other inference-time optimisers. • Experience with AWS or GCP ML services and streaming data such as Kafka or Kinesis. • Experience implementing agentic AI. • Familiarity with MLOps practices including CI/CD and model versioning.