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Shopify·Machine Learning Engineer·Take-home Assignment·Intermediate

Intermediate
May 2026

Summary

Take-home assignment for an ML Engineer role at Shopify that turned out to be less about machine learning and more about whether you actually know how to use Git like a professional. One question, very procedural, but it covered a lot of ground.

Questions Asked (1)

Q1

Walk through your complete Git and tooling workflow for a take-home project: setting up your IDE and SDK, cloning a repo, branching, building from scratch, writing and running unit tests, committing, pushing, opening a pull request, and configuring CI to run tests on each push.

Technical Trade-offsSystem DesignAPI & Integrations
Author's notes

This felt like a lot to cover and I kept second-guessing how much detail they actually wanted.

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AI HintsAI Generated

Suggested Approach

Structure your answer as a chronological walkthrough of the entire workflow, from environment setup to CI configuration, emphasizing reproducibility and automation. Highlight how each step supports collaboration and code quality, and mention specific tools and commands you use. Conclude by tying your workflow back to the role's requirements, such as testing ML code and integrating with CI.

Pro tip: Demonstrate maturity by mentioning how you handle common pitfalls, such as dependency conflicts or flaky tests, and how you ensure your workflow is reproducible for reviewers. Also, note that you version control not just code but also environment files (e.g., requirements.txt, environment.yml) to make the project easy to set up.

1. Environment Setup

Describe how you set up your IDE (e.g., VS Code, PyCharm) and SDK (e.g., Python, Node.js) with necessary plugins and extensions. Mention using virtual environments or containers for isolation.

2. Repository and Branching

Explain cloning the repo, creating a feature branch with a descriptive name, and following branching conventions (e.g., GitFlow, GitHub Flow).

3. Building and Testing

Walk through building the project from scratch (e.g., installing dependencies, compiling) and writing/running unit tests locally. Mention test frameworks (e.g., pytest, unittest) and how you ensure tests pass before committing.

4. Committing and Pushing

Describe your commit strategy (e.g., atomic commits with clear messages) and pushing to the remote branch. Mention using pre-commit hooks for linting or formatting.

5. Pull Request and CI

Explain opening a pull request with a detailed description, and configuring CI (e.g., GitHub Actions, CircleCI) to run tests on each push. Mention how you handle CI failures and iterate.

Key Points to Mention

  • Use of virtual environments (venv, conda) or Docker for reproducible setups.
  • Branch naming conventions and keeping branches focused on a single feature.
  • Writing unit tests with frameworks like pytest and ensuring high coverage.
  • Commit message best practices (e.g., Conventional Commits) and atomic commits.
  • CI configuration to run tests automatically on push, with status checks on PRs.
  • Handling secrets and environment variables securely in CI.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.