Sr. Engineer

4 days ago

Mumbai, India TIH | IIT Bombay Full time

Job Description:

  • Develop image-based classification models (CNNs, transfer learning, object detection, segmentation, vision).
  • Conduct data preprocessing, augmentation, and annotation workflows for image datasets.
  • Design, train, and validate deep learning architectures for feature identification using CNN, ResNet, EfficientNet, YOLO, U-Net, Mask R-CNN, ViT/Swin Transformer.
  • Develop clean, modular, and production-ready code for model training, inference, and deployment.
  • Collaborate with domain experts to translate agricultural knowledge into AI models.
  • Support integration of models with mobile application (through APIs and deployment-ready formats like TensorFlow Lite / ONNX).
  • Write unit tests, integration tests, and documentation to support long-term use of the framework.
  • Document methodologies, benchmarking reports, and prepare technical handover materials.


Minimum Qualifications and Experience:

  • B.Tech in Computer Science, Electronics and Communications with 3 - 5 years of experience.

OR

  • M.Tech with minimum 2 - 3 years of experience in Embedded system design.


Required Expertise:

  • Hands-on experience in Python.
  • ML/DL Frameworks - PyTorch, TensorFlow, Keras.
  • Proficiency in computer vision techniques – CNNs, object detection (YOLO/SSD), segmentation (U-Net/Mask RCNN), Vision Transformers (ViT, Swin Transformer, DeiT).
  • Libraries: NumPy, Pandas, OpenCV, Scikit-learn, Matplotlib/Seaborn.
  • Knowledge of model optimization for deployment (quantization, pruning, TensorFlow, Lite, ONNX).
  • Experience in developing APIs (Flask/FastAPI) for model serving.
  • Familiarity with ETL processes, data pipelines, and statistical validation methods.
  • Basic understanding of Docker and version control (Git) and experience with MLOps tools.
  • Ability to write production-grade Python code following best practices (modular design, logging, testing, error handling).


Preferred Skills:

  • Prior work in agriculture/agronomy-related AI projects.
  • Experience with cloud platforms (AWS/GCP/Azure).

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