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Lead Computer Vision Engineer

3 months ago

Pune, India Allianz Services Full time

Responsibilities

  • Team Leadership: Lead and mentor a team of computer vision engineers, providing technical guidance and support.
  • Project Management: Oversee the entire project lifecycle, from requirements gathering to deployment and maintenance.
  • Solution Architecture: Design, develop, and implement robust computer vision algorithms and models to address complex image analysis challenges.
  • Client Interaction: Build strong relationships with clients, understand their needs, and translate them into technical requirements.
  • Research and Development: Know-how of the latest advancements in computer vision and machine learning, exploring new technologies and techniques.
  • Model Development: Develop, train, and deploy state-of-the-art computer vision models, including deep learning architectures like vision transformers.
  • Data Analysis: Analyze and interpret large datasets to extract meaningful insights and improve model performance.
  • Performance Optimization: Optimize computer vision models for speed, accuracy, and efficiency.

Qualifications

  • B.Tech or master's in computer science, Machine Learning, or a related field.
  • Minimum 7 years of overall experience in software development and minimum 3-4 years of hands-on experience in computer vision and image analytics.
  • Proven experience in leading and mentoring technical teams.
  • Strong proficiency in Python, C++, or other relevant programming languages.
  • Expertise in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
  • In-depth knowledge of computer vision techniques, including image processing, object detection, image segmentation, and image recognition.
  • Experience with cloud platforms (AWS, GCP, Azure) and GPU computing.
  • Strong problem-solving and analytical skills.
  • Work with data engineers and analysts to source, analyse & engineer features, perform data augmentation.
  • Excellent communication and interpersonal skills.
  • Experience with vision transformers and other cutting-edge computer vision models is a plus.
  • Experience on Fraud analytics is preferred.



Key competencies:

  • Image Processing: Filtering, enhancement, restoration, geometric transformations
  • Feature Extraction: SIFT, SURF, HOG, LBP, and other traditional methods.
  • Object Detection: Faster R-CNN, YOLO, SSD, RetinaNet, and their variants.
  • Image Segmentation: U-Net, Deep Lab, Mask R-CNN.
  • Generative Adversarial Networks (GANs): Image generation, style transfer.
  • Attention Mechanisms: Transformer-based models, Vision Transformers.
  • Image Classification: Convolutional Neural Networks (CNNs), ResNet, VGG, Inception.
  • Image Registration: Aligning images from different sources.
  • Data Preprocessing: Data cleaning, augmentation, normalization.
  • Model Evaluation: Metrics, hyperparameter tuning, cross-validation.