Machine Learning Engineer

Department: Engineering

Location: Bogota, New York, Sao Paulo, San Francisco, Denver

Employment Type: FullTime

About Canals

Canals builds software for wholesale distributors, helping them operate more efficiently through automation and AI.

Our customers are the companies responsible for moving the materials that power the real economy; electrical supplies, plumbing products, roofing materials, HVAC equipment, and more. Every day, thousands of people rely on Canals to help process orders, manage purchasing, handle accounts payable, and streamline critical business workflows.

We're a profitable, rapidly growing company with a team of roughly 140 people distributed across North and South America. We care deeply about building great products, hiring exceptional people, and creating an environment where talented individuals can do the best work of their careers.

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 building software that solves real problems for an industry that keeps the world running. Our customers rely on our platform every day to operate their businesses.

We've found strong product-market fit and continue to grow quickly, creating opportunities for people who want to have a meaningful impact on the trajectory of a company.

We believe great people build great companies. That's why we invest heavily in hiring, development, and creating an environment where talented individuals can do the best work of their careers.

You'll work alongside ambitious, thoughtful teammates who care deeply about what they do, challenge each other directly, and have a lot of fun along the way.

We value ownership, transparency, and continuous improvement. Good ideas can come from anywhere, and people are trusted to make things happen.

We're remote-first, flexible, and distributed across North and South America, bringing together talented people from a wide range of backgrounds and experiences.

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.