Software Engineer Intern, Machine Learning (Summer 2027)

Résumé du poste

Contribute to the design, development, and testing of machine learning models while writing production-level code for ML pipelines. Collaborate with product managers and data scientists to frame business problems and communicate experimental findings.

Détails du poste

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.

Ce que vous ferez

Contribute to the design, development, and testing of machine learning models while writing production-level code for ML pipelines. Collaborate with product managers and data scientists to frame business problems and communicate experimental findings.

Exigences

Candidates must be currently pursuing a Bachelor's, Master's, or PhD in Computer Science or a related field at a Canadian university with a graduation date between December 2027 and Summer 2028. Applicants need strong Python programming skills and practical experience with machine learning libraries and workflows.

Avantages

• Mental health benefits • Paid time off • Sick time off • Subsidized commuter benefits • Lyft ride credits

Compétences indiquées

• Résolution de problèmes · Souhaitée
• Collaboration · Souhaitée
• Pipeline Development · Souhaitée
• Analyse de données · Souhaitée
• Apprentissage automatique · Souhaitée
• Communication · Souhaitée
• Python · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Machine learning
• Python
• Scikit-learn
• Tensorflow
• Pytorch
• Keras
• Mxnet
• Data analysis
• Software design
• Pipeline development
• Problem solving
• Research
• Collaboration
• Communication
• Resourcefulness
• Pipelines
• Workflow Management
• Curiosity
• Time Off Management
• Apache MXNet
• Quick Learning
• Artificial Intelligence
• Mental Health
• Computer Science
• Disabilities
• Interpersonal Communications
• Problem Solving
• Python (Programming Language)
• Machine Learning
• Object-Oriented Programming (OOP)
• TensorFlow
• Software Systems
• Software Quality (SQA/SQC)
• Keras (Neural Network Library)
• Scikit-Learn (Python Package)
• PyTorch (Machine Learning Library)

Domaines d’emploi

• Software
• Technology
• Data & Analytics
• Engineering
• Transportation
• Machine Learning Software Engineer
• Machine Learning Engineer
• Software Developers
• Computer and Information Research Scientists