Senior Software Engineer - Data & Ml Platform

GoMaterials is one of Canada's fastest-growing companies, recognized by Deloitte, the Globe & Mail, and the Lazaridis Scaleup Program. We’re revolutionizing how landscape contractors source plant and hardscape materials through a B2B marketplace that simplifies procurement in a traditionally outdated industry.
Since our inception, we have helped landscapers save time, money, and stress and plant over 1.5 million plants and trees. Led by a young and eager group of entrepreneurs, GoMaterials is aggressively expanding across North America. We are therefore looking for amazing people to add to our team!
About the RoleWe’re looking for a
Senior Software Engineer
to own and evolve the production systems and data infrastructure supporting our Machine Learning (ML) and Operations Research (OR) work.
This is a hands-on role combining
backend engineering, cloud infrastructure, and data engineering. You’ll work closely with ML and OR specialists to turn models and optimization solutions into reliable production systems.
You’ll join a small team where you’ll have significant ownership and influence over architecture, tooling, and how our platform evolves.
What You’ll Do
Own and improve backend services and production infrastructure running in Azure.
Build and maintain reliable data pipelines and our internal analytical/data platform.
Manage cloud infrastructure, deployments, CI/CD, monitoring, and infrastructure-as-code.
Turn ML and OR prototypes into reliable, production-ready services and workflows.
Build internal APIs, services, and tooling as the team’s needs evolve.
Improve system reliability, scalability, testing, and engineering practices.
Partner with ML, OR, Product, and Engineering on technical design and implementation.
What We’re Looking For
Strong Python and SQL skills.
Experience building and owning production backend services and data pipelines end to end.
Hands-on experience with Azure or another major cloud platform.
Experience with infrastructure-as-code such as Terraform or Bicep.
Strong understanding of APIs, CI/CD, automated testing, monitoring, and modern software engineering practices.
Comfort working with ML or optimization codebases—you don’t need to build the models, but you should be able to help bring them into production.
Experience taking ownership of existing production systems and improving them over time.
A degree in a relevant technical field or equivalent practical experience.
Nice to HaveExperience with any of the following is a plus, but not required:
Delta Lake, Parquet, or lakehouse architectures
DuckDB, Polars, or dbt
Airflow, Dagster, Prefect, or Durable Functions
Kubernetes or distributed workloads
DevOps/SRE practices
Optimization, logistics, transportation, or large-scale ML systems
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