Senior ML Engineer - Remote, End-to-End Pipelines

Canals; Bogotá; Presencial; COP 120.000.000 - 180.000.000; Jornada completa

Descripción de la vacante

Canals is seeking a senior-level Machine Learning Engineer to design, build, and maintain scalable ML models that automate logistics processes for our wholesale-distributor customers. You will own projects end-to-end from problem definition and data exploration to model deployment and monitoring in production.

Join a remote-first, fast-growing team, collaborate with engineering, and mentor others while driving real-world impact with AI at Canals.

Formación

• Senior-level experience building and deploying machine learning models in production.
• Experience designing scalable data pipelines and working with large datasets.
• Strong Python skills with ML frameworks and data tools.
• Ability to guide and unblock others, providing code reviews and architectural feedback.
• Experience in fast-paced, product-focused environments.

Responsabilidades

• Design, build, and maintain scalable ML models for logistics processes.
• Own projects end-to-end from problem definition to deployment and monitoring.
• Collaborate with engineering to align ML work with customer needs and value.
• Mentor and review code to ensure reproducibility, quality, and performance.
• Evaluate tools and frameworks to improve ML infrastructure and workflows.
• Help shape Canals' future as the company scales with customers.

Conocimientos

Python

ML frameworks

Data pipelines

Code reviews

Leadership/mentoring

Herramientas

scikit-learn

PyTorch

TensorFlow

Pandas

Spark

MLOps

Descripción del empleo

Canals is seeking a senior-level Machine Learning Engineer to design, build, and maintain scalable ML models that automate logistics processes for our wholesale-distributor customers. You will own projects end-to-end from problem definition and data exploration to model deployment and monitoring in production.

Join a remote-first, fast-growing team, collaborate with engineering, and mentor others while driving real-world impact with AI at Canals.