Machine Learning Engineer

About 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 and shaping product features that deliver real‑world impact.

Key responsibilities

• 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.

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 real, measurable customer value.
• Strong Python skills with knowledge of ML frameworks such as scikit‑learn, PyTorch, TensorFlow and data tools like Pandas and 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.

Required skills

• Python
• scikit‑learn
• PyTorch
• TensorFlow
• Pandas
• Spark

What we offer

• We build software that solves real problems for an industry that keeps the world running.
• Strong product‑market fit and rapid growth create opportunities to make a meaningful impact.
• We invest heavily in hiring, development and an environment where talented individuals can do their best work.
• Remote‑first, flexible and distributed across North and South America.
• Equal opportunity employer committed to diversity and inclusion.