Job Title: Machine Learning Engineering Intern

Job Summary: We are seeking a skilled Machine Learning Engineering Intern to join our team. The ideal candidate will have a passion for developing and implementing state-of-the-art machine learning algorithms for image recognition and natural language processing tasks. In this role, you will use various machine learning libraries such as PyTorch, Keras, TensorFlow, and state-of-the-art natural language processing algorithms and libraries, such as FastText, flairNLP, NLTK, and spaCy, to develop, train, and evaluate machine learning models.

 

Responsibilities:

  • Design, develop, and implement machine learning algorithms for image recognition and natural language processing tasks.
  • Use machine learning libraries such as PyTorch, Keras, TensorFlow to build and train models.
  • Use state-of-the-art natural language processing algorithms and libraries, such as FastText, flairNLP, NLTK, spaCy, to build and train NLP models.
  • Collaborate with cross-functional teams to collect and pre-process data and ensure data quality.
  • Evaluate and improve the accuracy and efficiency of existing models.
  • Keep up to date with the latest developments in the field of machine learning and natural language processing and integrate them into our product development cycle.

 

Requirements:

  • Must be currently enrolled in a computer science or related program and eligible for internship credit.
  • Strong proficiency in Python programming and machine learning libraries such as PyTorch, Keras, TensorFlow.
  • Strong understanding of natural language processing algorithms and libraries such as FastText, flairNLP, NLTK, spaCy.
  • Strong analytical and problem-solving skills.
  • Excellent communication and collaboration skills.

 

Work Schedule and Location:

  • Full-time internship with flexible work hours.
  • This position is fully remote.

 

Compensation:

  • This is an unpaid internship for academic credit.
  • Opportunities for growth, mentorship, and learning from experienced professionals.