Machine Learning Intern

Found in: Talent IN C2 - 3 weeks ago

Pune, India CCTECH Full time

We are currently seeking a motivated and passionate individual to join our team as a Machine Learning Intern. This internship offers a unique opportunity to work closely with experienced data scientists and engineers in a dynamic and innovative environment. As an ML intern, you will have the chance to contribute to cutting-edge projects, gain hands-on experience with state-of-the-art machine learning techniques, and collaborate with cross-functional teams to solve real-world challenges.


Duration Of Internship: 4 Months

Responsibilities: 
  • Collaborate with our team of data scientists and engineers to develop and deploy machine learning models and algorithms. 
  • Implement and evaluate various machine learning techniques, including supervised and unsupervised learning methods, for solving real-world problems. 
  • Conduct data preprocessing, feature engineering, and model evaluation to ensure the accuracy and robustness of machine learning models. 
  • Utilize deep learning frameworks such as PyTorch, TensorFlow, and Hugging Face for developing advanced neural network architectures. 
  • Work on computer vision tasks such as image processing, object detection, and tracking to extract meaningful insights from visual data. 
  • Apply natural language processing techniques for text classification, natural language understanding (NLU), summarization, and similarity analysis. 
  • Collaborate with cross-functional teams to integrate machine learning solutions into existing products and services. 
  • Document and communicate technical concepts and findings effectively to both technical and non-technical stakeholders. 


Requirements
  • Python programming language and good with libraries like matplotlib, seaborn, pandas, and NumPy. 
  • Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or Hugging Face. 
  • Hands-on experience with machine learning algorithms for supervised and unsupervised learning tasks. 
  • Solid foundation of statistical concepts including inferential statistics, hypothesis testing, and probability distributions. 
  • Strong understanding of Linear Algebra & Calculus. 
  • Knowledge of deep learning architectures like ANN, CNN, Transformers, LLM. 
  • Hands-on with one of the below deep learning domain: 
    Computer Vision tasks: image processing, OCR, object detection and tracking. 
    NLP tasks: text classification, summarization, similarity analysis, text-generation. 
  • Strong research skills with the ability to critically analyze scientific papers and literature related to machine learning and AI. 
  • Good to have experience with the below: 
    Participated in Kaggle or any ML hackathons. 
    Exposure to ML cloud service on AWS/Azure/GCP. 
    Explored Langchain, LlamaIndex, Vector stores. 


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