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Machine Learning Engineer

Roles & Responsibilities

  • Senior-level experience building and deploying machine learning models in production environments.
  • Experience designing scalable data pipelines and working with large datasets.
  • Strong Python skills with knowledge of ML frameworks (scikit-learn, PyTorch, TensorFlow) and data tools (Pandas, Spark).
  • Ability to guide and unblock others, providing thoughtful code reviews and architectural feedback.

Requirements:

  • Design, build, and maintain scalable ML models to automate logistics processes for customers.
  • Own projects end-to-end, from problem definition and data exploration to deployment and monitoring in production.
  • Collaborate closely with engineering teams to align ML work with customer needs and deliver features that drive business value.
  • Serve as a technical leader and mentor, reviewing code and ensuring reproducibility, quality, and performance.

Job description

About Canals

Canals is a fully remote, profitable startup transforming the industrial supply chain ($10T industry) with AI. Our platform seamlessly integrates with the systems distributors already use, automating tedious tasks and reducing failure points in moving physical goods across the globe.

We’re a 70-person team (~45 in engineering), located across North and South America.

The Role

Our customer base is expanding fast, and AI is central to how we scale and deliver value. We’re looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world impact.

What You’ll Do

  • Design, build, and maintain scalable machine learning models that improve and automate logistics processes for our customers.

  • Own projects end-to-end, from problem definition and data exploration to model deployment and monitoring in production.

  • Collaborate closely with engineering teams to align ML work with customer needs and deliver features that drive business value.

  • Serve as a technical leader and mentor within the ML area, reviewing code and ensuring best practices for reproducibility, quality, and performance.

  • Evaluate and implement tools and frameworks to improve our ML infrastructure and workflows.

  • Help shape the future of Canals as we continue scaling with our customers.

What You'll Bring

  • Senior-level experience building and deploying machine learning models in production environments.

  • Experience designing scalable data pipelines and working with large datasets.

  • Comfort taking ownership of projects and ensuring models deliver real, measurable customer value.

  • Strong Python skills with knowledge of ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow) and data tools (e.g., Pandas, Spark).

  • Ability to guide and unblock others, providing thoughtful code reviews and architectural feedback.

  • Experience working independently in a fast-paced, product-focused environment.

  • Previous experience in high-growth startups or small teams is a plus.

  • Familiarity with MLOps practices and tools is a plus.

Why Join Canals

  • We're profitable: stability without the chaos of venture pivots.

  • Real-world impact: your work improves global supply chains, saving customers time and reducing waste.

  • Strong engineering culture: we invest in quality and documentation to keep moving fast sustainably.

  • Culture of ownership: moving fast while putting quality first

  • Remote-first, flexible work environment across North and South America.

  • Stellar product-market fit with tons of customer love

  • All star team with diverse backgrounds to collaborate with and learn from

Canals.ai is an equal opportunity employer. In addition to EEO being the law, it is a policy that is fully consistent with our principles. All qualified applicants will receive consideration for employment without regard to status as a protected veteran or a qualified individual with a disability, or other protected status such as race, religion, color, national origin, sex, sexual orientation, gender identity, genetic information, pregnancy or age.

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