Software Engineer Intern, Machine Learning (Summer 2027)

Lyft
Toronto, Canada
On-siteCareer-pivot friendly

Who this role is best for

Geared toward students with ML research experience comfortable with building production-level ML pipelines.

Best fit for

  • Students with ML research experience and a focus on production-level pipeline development
    — “proven ability to effectively turn research ML papers into working code”
  • Candidates who thrive in collaborative environments and can translate ML concepts into business contexts
    — “Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context”
  • Individuals who are comfortable working with large-scale data systems and have a strong software engineering mindset
    — “engineer at heart with a high degree of comfort in designing software systems and producing high-quality code”

Things to consider

  • In-office presence is required at least 3 days per week, including specific days
    — “work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays”
  • Candidates must be enrolled in a Canadian university and graduate between December 2027 and Summer 2028
    — “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)”

How to stand out

  • Highlight end-to-end ML workflow experience and projects demonstrating production-level code
    — “practical knowledge of how to build efficient end-to-end ML workflows”
  • Emphasize specific ML library experience, especially with scikit-learn, Tensorflow, or PyTorch
    — “Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, etc.”
  • Demonstrate independent problem-solving skills through examples of research or self-directed learning
    — “willingness to figure things out independently through research or collaboratively through brainstorming”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Individual

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • model design and implementation
  • code quality
  • collaboration with cross-functional teams
Typical background
computer sciencedata sciencemachine learning

Skills & requirements

Required

Machine LearningPythonTensorFlowPyTorchMl Workflows

Preferred

Data AnalysisModel Training

Stack & domain

Pythonscikit-learnTensorFlowPyTorchKerasMxnet

About the role

Original posting from Lyft

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 improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. 

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 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

Benefits:

Mental health benefits

In addition to holidays, interns receive 2 days paid time off and 3 days sick time off

Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $46 - CAD $53 per hour. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This is a new position.

Source: Lyft careers

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