TL;DR

Staff MLOps Developer (Fintech): Lead development of AI/ML pipelines and infrastructure for risk and fraud detection in a large fintech platform with an accent on automated model recalibration, AI foundation model productionization, and secure ML operations. Focus on designing scalable, secure ML systems, model explainability, and deploying advanced models in finance.

Location: Remote (Canada)

Company

%hirify_global% is Canada's largest fintech company focused on transparent, low-cost financial services with over 3 million users and $100 billion in assets under management.

What you will do

Implement and deploy automated pipelines for model recalibration and re-fitting, starting with fraud detection models.
Contribute to development and productionization of a foundational AI model processing diverse client signals into embeddings for multiple applications.
Drive model explainability initiatives to meet regulatory requirements and enable faster deployment.
Lead MLOps security and infrastructure efforts to build robust, scalable, and secure ML systems protecting against adversarial threats.
Collaborate across teams to enhance end-to-end modeling infrastructure and maintain advanced models in production.

Requirements

Must have 5+ years experience in data science or machine learning engineering with finance domain expertise.
Proficiency in Python and ML libraries such as PyTorch, TensorFlow, LightGBM, and Scikit-Learn.
Experience designing and owning ML platforms from prototyping to deployment and maintenance.
Strong data engineering skills including handling large datasets and data pipelines.
Familiarity with deep learning, LLM concepts, GPU optimization, and responsible AI practices.
Experience with cloud platforms (AWS, SageMaker), distributed systems, containerization (Docker, Kubernetes), workflow orchestration (Airflow), and CI/CD tools.

Culture & Benefits

Competitive salary with top-tier health benefits and life insurance.
Retirement savings matching plan.
20 vacation days plus unlimited sick and mental health days.
Wellness and professional development budgets up to $1,500 per year each.
90 days international work program in eligible countries.
Inclusive employee resource groups and company-wide wellness days off.