Who we are:
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source plant and hardscape materials through a B2B marketplace that simplifies procurement in a traditionally outdated industry.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 role:
In this role, you will work at the intersection of data engineering, cloud infrastructure, and applied research, supporting advanced Machine Learning (ML) models, including supervised and unsupervised learning, regression, and classification, and Operations Research (OR) models for optimization and decision-making. You will build and maintain scalable data pipelines, set up and optimize infrastructure in Azure, with Azure ML Studio as the primary platform, ensure high standards of code quality, and contribute to ML/OR project validation and monitoring to accelerate experimentation and deployment.
This role is ideal for a strong developer who enjoys solving complex, real-world problems, thrives in a fast-paced environment, and wants to make a direct impact on the success of cutting-edge AI and optimization solutions.
What You’ll Do
- Design and maintain robust ETL/ELT pipelines for large and complex datasets.
- Deploy and scale ML/OR models in Azure using Azure ML Studio, DevOps, and containerization.
- Build automated validation, monitoring, and benchmarking pipelines to ensure models are accurate, reliable, and robust.
- Collaborate closely with Data Scientists, Engineers, and Product teams to integrate AI solutions into core products.
- Own projects end-to-end, mentor peers, and help define best practices for code quality and model governance.
What You’ll Need
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or related field.
- Strong programming skills in Python, plus experience with Java, C++, or similar languages.
- Solid understanding of data pipelines, APIs, and distributed systems.
- Hands-on experience with SQL/NoSQL databases and workflow orchestration tools (e.g., Airflow, Prefect, Luigi).
- Proven experience working with Azure services, including:
- Azure ML Studio, Azure Data Factory / Synapse, Azure Blob Storage, Data Lake, and Event Hub.
- Azure DevOps for CI/CD and infrastructure automation.
- Experience in ML model validation, evaluation, and monitoring.
- Strong knowledge of Git, CI/CD, automated testing, and code quality practices.
- Excellent problem-solving and collaboration skills.
Preferred Qualifications
- Experience with Azure Batch and Kubernetes for large-scale distributed workloads.
- Knowledge of data governance and security best practices in Azure.
- Prior work in optimization problems, transport/logistics, or large-scale ML systems.
- Exposure to DevOps/SRE practices for performance monitoring and reliability.
From day one, you get to...
💡 Share your ideas and actually see them come to life
🌱 Grow with us through learning & promotion opportunities
🏝️ Enjoy solid health benefits & time off (3 weeks + 1 week during the holiday break)
💰 Get a piece of the pie with equity after your first year
🎉 Work with a fun, tight-knit team that celebrates wins together. Want to learn more? Check out our
culture code.
Ready to apply?
If you think you’d be a great fit at our company and are passionate about this job, we want to hear from you!