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Software Engineer Intern, Machine Learning (Summer 2027)

Lyft Australia
Toronto, Canada Full Time Negotiable Sep 17, 2026

About the Job

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to im...

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!

Key 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
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 2027 and Summer 2028 (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 2027 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

Qualifications

Experience: 2 years experience
Education: Postgraduate

Apply now

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