Job Description

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source plant and hardscape materials through a B2B marketplace that simplifies procurement in a traditionally outdated industry.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, infrastructure, and applied research, supporting advanced Machine Learning (ML) and Operations Research (OR) projects. You will be responsible for building and maintaining scalable data pipelines, setting up and optimizing infrastructure in Azure (with Azure ML Studio as the primary platform), ensuring high standards of code quality, and contributing to ML project validation and monitoring to accelerate experimentation and deployment.

This role is ideal for a strong developer who thrives in a fast-paced environment and wants to contribute directly to the success of cutting-edge data products.

What You'll Do

Data Pipeline Development

Design, build, and maintain reliable ETL/ELT pipelines for structured and unstructured data. Ensure data quality, integrity, and availability for ML and OR model training and evaluation. Implement monitoring and logging for data workflows.

Infrastructure & Deployment (Azure Focus)

Set up and maintain data science infrastructure in Azure, with a strong focus on Azure ML Studio for ML/OR workflows. Productionize AI models in the cloud and ensure its scalability. Automate environment provisioning, dependency management, and CI/CD pipelines on Azure DevOps. Support containerization and orchestration (Docker, Kubernetes, Azure Batch, Azure Container Registry). Optimize compute resource usage across Azure VMs, clusters, and ML pipelines.

ML Project Validation & Monitoring

Implement validation frameworks for ML and OR experiments to ensure reproducibility, correctness, and robustness. Develop automated pipelines for model evaluation, testing, and benchmarking against baselines. Build monitoring dashboards in Azure ML Studio and related tools to track model performance, drift, and system reliability. Ensure compliance with data governance, versioning, and auditability standards.

Code Quality & Collaboration

Establish and enforce coding standards, version control practices, and automated testing for ML/OR codebases. Partner with Data Scientists and OR Engineers to transform research prototypes into production-ready code. Conduct peer code reviews and mentor team members on best practices.

Cross-Functional Contribution

Collaborate with Product and Engineering teams to integrate ML/OR solutions into core products. Provide technical input into design discussions, performance optimization, and scalability planning.

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 for ML/OR experiments, training, deployment, and monitoring. Azure Data Factory / Synapse for data pipelines. Azure Blob Storage, Data Lake, and Event Hub for data ingestion and storage. 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...

uD83DuDCA1 Share your ideas and actually see them come to life
uD83CuDF31 Grow with us through learning & promotion opportunities
uD83CuDFDD? Enjoy solid health benefits & time off (3 weeks + 1 week during the holiday break)
uD83DuDCB0 Get a piece of the pie with equity after your first year
uD83CuDF89 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!