Machine Learning Student Internship Opportunity

4 weeks ago


Toronto, Ontario, Canada Avoltacanada Full time
About Avolta

Avolta is a pioneering startup dedicated to revolutionizing automotive anti-theft security. Leveraging cutting-edge technologies, we are committed to developing innovative solutions that safeguard vehicles from theft and unauthorized access.

Job Overview

We are seeking a talented Machine Learning Student Intern to join our research and development team and contribute to our mission. This internship offers a unique opportunity for hands-on experience in the field of machine learning, working alongside experienced professionals to enhance your skills and knowledge.

Key Responsibilities
  1. Collaborate with the research and development team to understand the requirements and objectives of the machine learning projects.
  2. Assist in the collection, preprocessing, and analysis of relevant data to train and validate machine learning models.
  3. Develop and implement machine learning algorithms for vehicle security and anti-theft applications.
  4. Fine-tune existing machine learning models and explore new approaches to improve accuracy and performance.
  5. Stay updated with the latest advancements in machine learning and security to contribute to the team's knowledge base.
Requirements
  • Enrolled in a relevant undergraduate or graduate program in Computer Science, Machine Learning, Data Science, or a related field.
  • Solid understanding of machine learning fundamentals and algorithms.
  • Proficiency in programming languages such as Python and experience with machine learning libraries.
  • Familiarity with data preprocessing techniques and feature engineering.
  • Prior projects or coursework related to machine learning, computer vision, or security is a plus.
What We Offer

We do have plans on offering paid part- and full-time roles in the future, for which we will hire internally. Please note that our student internships are for students enrolled in Canadian colleges/universities only.



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