ML/AI Engineer

Role Description

AI is becoming central to how our customers operate, from automating repetitive workflows to making complex operational decisions faster and more accurately. As Canals continues to grow, we’re looking for an ML/AI Engineer to help build and scale intelligent systems across our platform. This is a highly applied role focused on shipping production-grade AI features that create measurable business value.

You’ll work at the intersection of machine learning, backend systems, and product engineering, building solutions that improve how wholesale distributors process orders, manage purchasing, classify documents, and automate critical workflows.

This role is ideal for engineers who enjoy owning AI products end-to-end: from experimentation and model development to deployment, monitoring, and iteration in production.

What You’ll Do

• Design, build, and deploy AI-powered product features across Canals’ core workflows.
• Develop and maintain LLM-powered systems, including agents, retrieval pipelines (RAG), and workflow automation.
• Build machine learning models for operational use cases such as classification, forecasting, anomaly detection, and recommendation systems.
• Own the full lifecycle of ML systems: data pipelines, experimentation, training, evaluation, deployment, and production monitoring.
• Work closely with product, operations, and customer teams to identify high-impact AI opportunities.
• Improve the scalability, reliability, and performance of AI infrastructure and inference systems.
• Establish best practices for prompt engineering, model evaluation, observability, and cost optimization.
• Collaborate with backend engineers to integrate AI systems deeply into product workflows.
• Help shape Canals’ long-term AI strategy as we expand automation across the platform.

Qualifications

• 4+ years of software engineering experience, with significant exposure to machine learning or applied AI.
• Strong backend engineering fundamentals and experience building scalable production systems.
• Hands-on experience shipping ML or LLM-powered products into production.
• Experience with Python and modern ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Experience working with LLM APIs and tooling (OpenAI, Anthropic, LangChain, LlamaIndex, or similar).
• Familiarity with vector databases, retrieval systems, and AI orchestration frameworks.
• Experience designing evaluation frameworks for AI quality, reliability, and performance.
• Strong understanding of API design, distributed systems, and cloud infrastructure.
• Ability to operate independently, move quickly, and take ownership in a product-driven environment.
• Strong product intuition and the ability to translate ambiguous business problems into technical solutions.

Nice to Have

• Experience building AI systems for operational workflows, ERP systems, or B2B SaaS.
• Experience fine-tuning models or working with open-source LLMs.
• Familiarity with document intelligence (OCR, extraction, classification).
• Experience with event-driven architectures and high-volume backend systems.
• Previous experience at high-growth startups or small, fast-moving teams.

Benefits

• We’re building software that solves real problems for an industry that keeps the world running.
• 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.
• At Canals, AI isn’t a side project; it’s becoming a core part of how we build.
• 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.