Python AND TensorFlow Machine Learning Intern - Virtual

Amazon

Available Locations: Brooks, Ontario

Job Description

Job Summary


Amazon is seeking a highly motivated Machine Learning Intern with a strong foundation in Python and TensorFlow to join our cutting-edge virtual internship program. This role is ideal for students or recent graduates eager to gain real-world experience working on impactful machine learning projects. As an intern, you will be collaborating with Amazon’s AI/ML teams to solve real business challenges, build intelligent systems, and innovate at scale.




Key Responsibilities



  • Assist in designing, developing, and optimizing machine learning models using Python and TensorFlow.

  • Collaborate with data scientists, software engineers, and research teams to analyze large datasets and generate meaningful insights.

  • Participate in end-to-end ML lifecycle, from data preprocessing and feature engineering to model deployment and evaluation.

  • Document model development processes and present findings to internal stakeholders.

  • Implement experiments to test model performance and validate hypotheses.

  • Contribute to automation of ML pipelines and continuous model improvement.




Required Skills and Qualifications



  • Proficiency in Python with hands-on experience in data science or machine learning projects.

  • Strong understanding of TensorFlow or similar ML frameworks (e.g., PyTorch, Keras).

  • Knowledge of data structures, algorithms, and object-oriented programming.

  • Ability to preprocess, clean, and manipulate large datasets.

  • Solid understanding of supervised and unsupervised learning techniques.

  • Strong communication and teamwork skills in a collaborative virtual environment.




Experience



  • Previous internship, personal, or academic projects involving machine learning or data science is highly desirable.

  • Familiarity with Amazon Web Services (AWS) such as S3, SageMaker, or Lambda is a plus.

  • Contributions to open-source ML projects or Kaggle competitions are an added advantage.




Working Hours



  • Flexible working hours (10–20 hours/week recommended)

  • Fully remote; suitable for candidates in any time zone

  • Collaborative meetings may require some overlap with Pacific Standard Time (PST)




Knowledge, Skills, and Abilities



  • Analytical mindset with attention to detail and a passion for problem-solving

  • Ability to work independently and take initiative on assigned tasks

  • Excellent written and verbal communication skills

  • Quick learner with a growth mindset and interest in AI innovations

  • Ability to manage time effectively in a self-paced remote setup




Benefits



  • Work with one of the world’s leading tech companies

  • Mentorship from senior data scientists and ML engineers at Amazon

  • Gain exposure to real-world machine learning projects and workflows

  • Amazon Internship Certificate upon successful completion

  • Networking opportunities within Amazon’s tech and innovation community

  • Potential pathway to full-time roles after graduation




Why Join Amazon’s Virtual Internship Program?


At Amazon, we are driven by the mission to be Earth’s most customer-centric company. By joining our internship program, you will be immersed in a culture of innovation, continuous learning, and impact-driven development. Our virtual internships provide an inclusive platform for global talent to thrive, contribute, and grow — regardless of location. You’ll gain not only technical skills but also professional development support in a highly respected global brand.




How to Apply


Ready to kick-start your machine learning career at Amazon? Follow these steps:



  1. Prepare your updated resume highlighting Python and TensorFlow experience.

  2. Include links to GitHub, Kaggle, or any portfolio showcasing your ML work.

  3. Click [Apply Now] on the Amazon Careers Portal and search for "Python AND TensorFlow Machine Learning Intern – Virtual"

  4. Submit your application with a short cover letter explaining why you’re a great fit.