Senior Data Scientist - Computer Vision

Job Summary :

Join our team as a Senior Data Scientist specializing in Computer Vision, where you will lead the design, development, and deployment of cutting-edge vision-based machine learning models. In this role, you will tackle complex real-world business challenges by building scalable AI solutions. We are looking for an expert with a deep understanding of image and video processing who can seamlessly bridge the gap between technical innovation and business impact.

Role & responsibilities :

• Develop and deploy sophisticated computer vision models for tasks including object detection, image classification, segmentation, OCR, and real-time video analytics.

• Manage large-scale datasets by overseeing collection, annotation strategies, cleaning, and data augmentation to ensure high-quality model training.

• Architect and optimize deep learning frameworks such as CNNs, Vision Transformers, GANs, and YOLO for production-ready environments.

• Collaborate with cross-functional engineering, product, and MLOps teams to integrate vision models into end to-end production pipelines.

• Enhance model performance and scalability through quantization, pruning, and conversion for edge deployment using ONNX or TensorRT.

• Execute rigorous experiments and statistical analyses, including A/B testing, to validate model accuracy and assess business outcomes.

• Keep abreast of state-of-the-art research in computer vision and deep learning to identify and implement innovative solutions for business problems.

• Mentor junior scientists and establish best practices for robust model development, evaluation, and documentation.

• Partner with data engineering to build high-performance, scalable data pipelines tailored for vision workloads.

Preferred candidate profile :

• 7+ years of professional experience in Machine Learning with a specialization in Computer Vision.

• Advanced degree (Master's or Ph.D. preferred) in Computer Science, Electrical Engineering, or a related quantitative field.

• Expert proficiency in Python and frameworks like PyTorch, TensorFlow, or Keras.

• Hands-on experience with CV libraries such as OpenCV, YOLO, Detectron2, and MMDetection.

• Strong background in CNNs, Vision Transformers (ViT), and image preprocessing techniques.

• Proven experience deploying models via Docker, Kubernetes, FastAPI, ONNX, and TensorRT.

• Skilled in cloud AI/ML services across AWS, GCP, or Azure (e.g., SageMaker, Vertex AI).

• Deep knowledge of data structures, algorithms, and software engineering best practices.