If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you!
Responsibilities:
- Contribute to the design, build, train and test of Machine Learning models
- Write production-level code to convert ML models into working pipelines
- Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context
- Analyze experimental and observational data, communicate findings to support decisions
- Participate in code and spec reviews to ensure code quality and distribute knowledge
Experience:
- Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required), with a graduation date between December 2026 and Summer 2027 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience
- Available during Summer 2026 for the internship in Toronto
- Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, etc.
- Strong programming skills in Python or a similar object oriented language
- Proven ability to effectively turn research ML papers into working code
- Practical knowledge of how to build efficient end-to-end ML workflows
- “Engineer at heart” with a high degree of comfort in designing software systems and producing high-quality code
- Curiosity and ability to quickly learn new concepts and technologies
- Strong problem solving mindset, resourcefulness, and willingness to figure things out independently through research or collaboratively through brainstorming
- Demonstrated oral and written interpersonal skills
