ML Engineering Intern (Python)

TL;DR

ML Engineering Intern (Python/Databricks): Building and maintaining production batch and streaming pipelines for risk intelligence and fraud detection with an accent on data processing and feature engineering. Focus on converting validated detection code into scalable production pipelines and developing internal AI-assisted automation tools.

Location: Must be based in Vancouver, BC (in person). No visa or relocation support provided.

Salary: $50,000 - $62,000 CAD (annualized, prorated for 6-month term)

Company

hirify.global provides advanced detection systems to prevent location spoofing, identity fraud, and suspicious device patterns for global clients.

What you will do

• Convert validated detection logic into production-ready batch and streaming pipelines using Python, PySpark, and Databricks.
• Design and implement testing and validation frameworks to ensure stability before production deployment.
• Develop and extend internal AI-assisted tools to automate engineering and operational workflows.
• Support multi-client rollouts of detection pipelines, including schema changes and deployment orchestration.
• Debug production issues and enhance system monitoring and observability.
• Build a "Governance Hub" system to track models, shipping checklists, and governance artifacts.

Requirements

• Degree in Computer Science, Software Engineering, Data Science, or equivalent technical experience.
• Strong software engineering foundation, including data structures, algorithms, Git, and clean code habits.
• Familiarity with cloud data platforms (Databricks, GCP, or AWS) and relational or NoSQL databases.
• Legal authorization to work in Canada is required.
• Comfortable working with AI-assisted development workflows (e.g., Claude Code).
• Excellent written and verbal communication skills for technical and non-technical collaboration.

Nice to have

• Prior internship experience with production code, data pipelines, or ML systems.
• Experience with PySpark or distributed data processing.
• Familiarity with pipeline orchestration (Airflow, Databricks Workflows) or streaming systems.
• Background in fraud detection, risk intelligence, or anti-abuse work.
• Experience building internal developer tools, CLI tools, or automation scripts.

Culture & Benefits

• Direct production impact from week one with code serving live clients.
• Strong mentorship structure featuring a dedicated buddy and weekly 1:1s with management.
• Direct access to senior leadership, including meetings with the co-founder.
• Clear conversion track to full-time SWE/MLE roles based on performance.
• Structured onboarding Boot Camp for product immersion and professional development.