🛠 Tech Stack

💼 About This Role

You'll build and scale ML systems for a fast-growing Canadian fintech serving over 800,000 users. Your work will power credit risk decisions and shape the future of our technology.

🎯 What You'll Do

• Design, develop, and deploy end-to-end ML pipelines.
• Implement MLOps best practices including CI/CD and model monitoring.
• Optimize models via feature engineering and hyperparameter tuning.
• Deploy and manage models on cloud platforms with Docker/Kubernetes.

📋 Requirements

• Proficiency in Python and ML libraries (Scikit-learn, LightGBM, PyTorch).
• Strong understanding of machine learning algorithms (supervised & unsupervised).
• Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker.
• Hands-on experience with data manipulation (Pandas, NumPy) and SQL.

✨ Nice to Have

• Knowledge of cloud-based deployment and infrastructure management.
• Experience with real-time and batch inference pipelines.
• Familiarity with containerization and orchestration tools.

🎁 Benefits & Perks

• 💰 Top of market compensation
• ⚕️ Comprehensive health, dental, vision
• 🖥️ $1,500 annual learning & home-office stipend
• 🧘🏼 $1,000 annual wellness stipend
• 🏝️ 20 annual PTO days + unlimited sick days

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Phone Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Onsite / Final Round· 60 min