Machine Learning Engineer
Design and operate the systems that make fraud detection possible, working across applied machine learning, data pipelines, and Go-based backend systems to deliver reliable, efficient, scalable solutions for 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 in production
- Turn raw data into production-ready features for fraud detection systems
- Collaborate with platform and backend engineers to integrate models
- 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 in Go or Python
- Hands-on applied ML experience with large datasets, including PyTorch or Scikit-learn
- 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 written and verbal English communication skills
- Bachelor's or Master's degree 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, dental, and vision insurance for employees and dependents
- 4% matching in 401k or RRSP
- MacBook Pro delivered to your door
- Home office setup stipend
- Monthly meal stipend
- Monthly social meet-up stipend
- Annual health and wellness stipend
- Annual learning stipend