Machine Learning Engineer

As a Machine Learning Engineer, you will design and implement ML models and data pipelines that power fraud detection in production. You will turn raw data into production-ready features, optimize models for scale and reliability, ensure security and privacy, and collaborate with engineers to deploy end-to-end solutions.

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 our 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

• 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

• Generous compensation in cash and equity
• Early exercise for all options, including pre-vested
• Work from anywhere: Remote-first Culture
• Flexible paid time off and Year-end break
• Health insurance, dental, and vision coverage for employees and dependents - US and Canada specific
• 4% matching in 401k / RRSP - US and Canada specific
• MacBook Pro delivered to your door
• One-time stipend to set up a home office — desk, chair, screen, etc.
• Monthly meal stipend
• Monthly social meet-up stipend
• Annual health and wellness stipend
• Annual Learning stipend