Applied ML

1 day ago

Mumbai, Maharashtra, India TIH | IIT Bombay Full time ₹ 15,00,000 - ₹ 25,00,000 per year

Job Description:

  • Development, adaptation, and implementation of AI/ML algorithms and frameworks, Prediction algorithms
  • Developing deep learning and machine learning algorithms (CNN, object detection, segmentation, SVM, AE)
  • Time series forecasting: AR, ARIMA, SARIMA, ES, Prophet, LSTM
  • 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 or any related field with 3-5 years of relevant experience

OR

  • M.Tech in Computer Science, Electronics and Communications or any related field with 2-3 years of relevant experience

Required Expertise:

  • Strong hands-on experience with Python and ML/DL frameworks (PyTorch, TensorFlow, Keras).
  • Proficiency in computer vision techniques – CNNs, object detection (YOLO/SSD), segmentation (U-Net/Mask R-CNN), 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)
  • Understanding of statistical analysis such as normality test, dicky fuller test etc

Location of work:

  • TIH-IoT, IIT Bombay Campus, Powai, Mumbai

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