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Machine Learning Engineer

canals · Bogota

New
Senior 🇬🇧 English
Python scikit-learn PyTorch TensorFlow Pandas Spark MLOps

Job description

About the role

Canals builds software for wholesale distributors, helping them operate more efficiently through automation and AI. Its customers include electrical supply, plumbing, roofing and HVAC companies, and the company is described as profitable and rapidly growing, with about 140 people spread across North and South America. It is looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, own end-to-end ML pipelines and shape product features that deliver real-world impact.

Key responsibilities

  • Design, build and maintain scalable machine learning models that improve and automate logistics processes for customers.
  • Own projects end-to-end, from problem definition and data exploration to model deployment and monitoring in production.
  • Collaborate with engineering teams to align ML work with customer needs and deliver features that drive business value.
  • Serve as a technical leader and mentor in the ML area, reviewing code and ensuring best practices for reproducibility, quality and performance.
  • Evaluate and implement tools and frameworks to improve ML infrastructure and workflows.

Required profile

  • 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 measurable customer value.
  • Ability to guide and unblock others, giving 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.

Required skills

  • Strong Python skills.
  • Knowledge of ML frameworks such as scikit-learn, PyTorch and TensorFlow.
  • Data tools such as Pandas and Spark.
  • Familiarity with MLOps practices and tools is a plus.

The company describes itself as remote-first and distributed across North and South America, and is an equal opportunity employer.

Questions fréquentes

Le salaire n'est pas communiqué publiquement par le recruteur. Vous pouvez postuler et négocier directement avec canals.
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Source : ats:ashby

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Published 2 hours ago

Expires 1 month from now

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