ML Platform Engineer Intern – Hybrid, Toronto

United States Digital Space LLC

Toronto

Hybrid

CAD 63,000 - 73,000

Part time

5 days ago
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Benefits offered by this job

Mental health benefits
2 days paid time off
3 days sick time off
Subsidized commuter benefits and the公司

Job summary

United States Digital Space LLC is seeking a student intern in Toronto to contribute to an ML platform in a hybrid in-office environment. You will design, train, and test ML models and write production-level code to turn models into working pipelines.

The role requires studies in CS or a related field at a Canadian university, with graduation dates between late 2027 and mid-2028, and strong Python skills. Expect collaborative work with cross-functional teams and opportunities to translate

Qualifications

  • Pursuing a bachelor’s, master’s, or PhD in Computer Science or a related technical field from a university in Canada (required).
  • Graduation date between Dec 2027 and Summer 2028 (required).
  • For master's candidates with a gap between degrees: less than 2 years of relevant full-time work experience.

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 ML Engineers to frame ML 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 knowledge sharing.

Skills

Python programming
ML libraries
Research to code translation
Good communication
Team collaboration

Education

Bachelor’s/Master’s/PhD in CS or related

Tools

scikit-learn
TensorFlow
PyTorch
Keras
MXNet

Job description

United States Digital Space LLC is seeking a student intern in Toronto to contribute to an ML platform in a hybrid in-office environment. You will design, train, and test ML models and write production-level code to turn models into working pipelines.

The role requires studies in CS or a related field at a Canadian university, with graduation dates between late 2027 and mid-2028, and strong Python skills. Expect collaborative work with cross-functional teams and opportunities to translate

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