Staff Software Engineer, Machine Learning Platform

Location: Remote in Canada or office-based in Toronto; office-assigned employees spend at least 50% of each month in the local office or with users. Remote employees regularly work from home and may attend meetings, on-sites, meet-ups, and events.

Salary: CA$208,000–CA$312,000 annual salary in the primary location. Additional compensation may include equity, bonuses, retirement plans, health benefits, and wellness stipends.

Company

Stripe provides financial infrastructure that helps businesses accept payments, grow revenue, and launch new business opportunities.

What you will do

• Own end-to-end architecture and system design for large, complex ML Platform projects.
• Define technical direction and long-term platform strategy for ambiguous, high-impact initiatives.
• Design systems for ML workflow orchestration, CPU and GPU infrastructure, model training, LLM fine-tuning, low-latency inference, feature stores, monitoring, and agent orchestration.
• Lead projects from requirements and design through implementation and production operation.
• Translate needs from ML engineers, data scientists, and product teams into scalable technical solutions.
• Drive cross-team MLOps improvements, advise senior leadership, and mentor engineers.

Requirements

• 10+ years of professional software development experience or equivalent domain expertise.
• Strong background in service-oriented architecture and large-scale distributed systems.
• Experience leading multi-team initiatives, providing technical direction, and mentoring engineers.
• Production experience building and operating ML platforms for model training, serving, orchestration, or ML data systems.
• Strong communication, product judgment, cross-functional collaboration, and comfort working autonomously in ambiguous environments.
• Hands-on experience using AI tools to accelerate software development.

Nice to have

• Experience with distributed ML training, accelerator-backed compute, training data pipelines, experiment tracking, model evaluation, feature stores, and model registries.
• Experience shipping machine learning models to production and rapidly iterating prototypes based on user feedback.
• Familiarity with LLMs, LLM application frameworks, agentic AI, retrieval-augmented generation, AWS, SageMaker, Bedrock, Databricks, or OpenAI.
• Experience working with geographically distributed teams or contributing to open source and self-directed technical projects.

Culture & Benefits

• Flexible choice between office-based and remote work within Canada.
• Remote work is primarily home-based, with access to in-person meetings, on-sites, meet-ups, and events.
• Work with ML engineers, data scientists, product teams, platform infrastructure teams, and senior leadership.
• Benefits may include equity, company bonuses, retirement plans, health benefits, and wellness stipends.