Machine Learning Engineer

You'll do more than build models — you'll design the systems that make fraud detection possible. Working across modeling, data pipelines, and backend systems built in Go, you'll ensure ML models run reliably, efficiently, and at scale. You'll combine applied ML with large-scale systems engineering, owning end-to-end solutions that tackle high-stakes, ever-evolving challenges in fraud and financial crime prevention.

Responsibilities

• Build and optimize data pipelines and backend services to process device and behavioral data in real time
• Develop and deploy ML models for fraud detection, ensuring they run reliably and efficiently in production
• Turn raw data into production-ready features that feed fraud detection systems
• Collaborate with platform and backend engineers to integrate models seamlessly
• Maintain high standards of security, privacy, and compliance
• Champion best practices in testing, documentation, and observability

Requirements

• 5+ years in software engineering, with strong backend experience (Go or Python)
• Hands-on experience with applied ML using large datasets (PyTorch, Scikit-learn, etc.)
• Strong SQL skills and familiarity with relational and non-relational databases
• Experience with end-to-end ML systems: feature pipelines, model deployment, monitoring, and iteration
• Excellent communication skills in English, both written and verbal
• Bachelor's or Master's in Computer Science, Engineering, or a related discipline

Benefits

• Equity compensation
• Early exercise for all options, including pre-vested
• Remote-first culture
• Flexible paid time off and year-end break
• Health insurance, dental, and vision coverage for employees and dependents
• 4% matching in 401k / RRSP
• MacBook Pro delivered to your door
• One-time stipend to set up a home office
• Monthly meal stipend
• Monthly social meet-up stipend
• Annual health and wellness stipend
• Annual learning stipend