Job Description:

  • Minimum 2 years of hands-on technical experience in implementing and developing machine learning (ML) solutions.
  • Proficiency in deep learning models, including CNN, RNN, LSTM, Transformer, Vision Transformer, BERT, OCR, and YOLO.
  • Expertise in Python frameworks such as Flask and FastAPI.
  • Proficient in deep learning frameworks like TensorFlow and PyTorch.
  • Responsible for training and validating both deep learning-based and statistical-based models, ensuring consideration of complexity, performance, and robustness.
  • Hands-on experience with packages and libraries such as scikit-learn and NLTK.
  • Experience in developing and fine-tuning applications using open-source machine learning management systems like LLAMA2.
  • Familiarity with model compression techniques like OpenVINO and TensorRT.
  • Skill set requirements include proficiency in Python, natural language processing (NLP), and optical character recognition (OCR).

This role requires a solid background in implementing and developing machine learning solutions, particularly with deep learning models. Candidates should be proficient in Python frameworks such as Flask and FastAPI, as well as deep learning frameworks like TensorFlow and PyTorch. Experience with training and validating various types of models, including deep learning-based and statistical-based ones, is essential. Additionally, familiarity with model compression techniques and open-source machine learning management systems is highly desirable. If you possess these skills and have a passion for leveraging machine learning to solve complex problems, we encourage you to apply.

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