Fintech jobs in Canada

About Us

Spring Financial is revolutionizing financial access for Canadians, providing smart credit-building, mortgage, and lending solutions. Millions struggle with high-interest debt and limited financial options—we’re here to change that.

As one of Canada’s fastest-growing fintech companies, annually we help 1 million customers explore their financing options with ease—online, via text, or over the phone. Our dynamic, innovative team thrives on collaboration, growth, and making a real impact.

To learn more about our products please visit our website here: www.springfinancial.ca.

NOTE: This is a full-time, permanent, hybrid position in downtown Vancouver, with 3 set days in the office and 2 WFH.

Job Overview

As a Machine Learning Engineer II, you independently design, build, and maintain machine learning systems that deliver impact for our customers and business. You are responsible for deploying reliable, scalable solutions — from credit scoring models to intelligent automation and LLM-powered features. You work across the stack to connect ML systems with real user value.

You own end-to-end workflows: from data ingestion and transformation to model training, validation, and online inference. You actively contribute to model quality, observability, and performance optimization. You also help standardize development practices, CI/CD, and deployment tooling for ML systems.

You are expected to integrate modern AI techniques — including LLM APIs, embeddings, and generative workflows — where appropriate, and help evaluate how they can enhance products and operations. You use AI development tools to accelerate delivery and improve testing and debugging. You also build and maintain automated data pipelines and model services, working across real-time and batch systems.

You work closely with product managers, data scientists, and business stakeholders to clarify problems, evaluate feasibility, and align technical solutions with strategic outcomes. You are a key contributor to the evolution of Spring’s ML platform and culture.

What You’ll Do

• Own development of production-grade ML and AI systems — from data to deployment.
• Build automated pipelines for training, feature engineering, and model serving.
• Use AI tools to improve development speed and integrate AI capabilities (e.g. LLMs) into products.
• Optimize systems for performance, latency, and cost.
• Collaborate with cross-functional stakeholders to scope projects and communicate results.
• Monitor, retrain, and improve models based on feedback and system metrics.
  
  

What You Should Already Have

• Experience deploying machine learning models into production systems.
• Proficiency in Python and tools such as scikit-learn, TensorFlow, PyTorch, or HuggingFace.
• Strong understanding of model lifecycle, MLOps, and data pipeline design.
• Skills in inference optimization.
• Ability to collaborate with data, product, and business teams on impactful ML features.
• Experience with testing, monitoring, and CI/CD for ML systems.
• Know-hows on cost/benefit analysis for different ML solutions, e.g. Lambda vs. Sagemaker Inference, OpenAI vs. xAI API.
• Comfortable working with AI technologies (LLMs, embeddings, etc.) in applied settings.
  
  

What We Will Give You

• Competitive annual salary ranging from $100,000 to $120,000+, reflective of experience and impact.
• Comprehensive benefits package, including extended health, dental, and vision coverage — with 100% of monthly premiums covered by the Spring.
• GRSP matching program to support your long-term financial goals.
• Transit-Friendly Employer (Transit allowance).
• A modern, collaborative workspace in the heart of downtown Vancouver.
• Ongoing career growth opportunities and the chance to help shape Spring Financial’s technology strategy and team culture.
  
  

Please note: Upon applying, our Talent Acquisition team will review your resume. If you qualify, we will reach out to learn more about your experience and answer any questions you may have about the role, benefits, compensation, and more. Due to high application volume, we may not be able to respond to everyone.

Thank you for your interest! We appreciate your time and look forward to reviewing your application!