Machine Learning Engineer

Canals

Machine Learning Engineer developing scalable AI models for logistics automation at Canals. Collaborating with engineering teams to deliver impactful machine learning features.

Posted 7/14/2026full-timeRemote • 🇨🇴 ColombiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying scalable machine learning models, with strong proficiency in Python and familiarity with ML frameworks and data tools. Capable of leading projects end-to-end while mentoring others and ensuring best practices in code quality and performance.

Highest-signal resume keywords

Machine Learning Model DeploymentPython ProgrammingScalable Data Pipeline DesignML Frameworks (Scikit-Learn, PyTorch, TensorFlow)MLOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData Pipeline DesignModel DeploymentData ExplorationCode Review

Soft Skills

Technical LeadershipMentoringCollaboration

Tools & Technologies

Scikit-LearnPyTorchTensorFlowPandasSpark

Industry Keywords

MLOpsProduction EnvironmentsLogistics Processes

Tech Stack

Tools & technologies

PandasPythonPyTorchScikit-LearnSparkTensorflow

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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 (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.
Familiarity with MLOps practices and tools is a plus.

Benefits

Comp & perks

We're a profitable, rapidly growing company
We care deeply about building great products
We invest heavily in hiring, development, and creating an environment where talented individuals can do the best work of their careers.