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Stripe

Staff Engineer, Machine Learning Infrastructure

Posted 21 Hours Ago
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Toronto, ON
Expert/Leader
Toronto, ON
Expert/Leader
As a Staff Engineer in Machine Learning Infrastructure at Stripe, you will lead technical projects that enhance ML development and MLOps. You will design system architecture, define project directions, mentor engineers, and collaborate across functions to improve the end-to-end ML lifecycle for the company.
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Who we areAbout Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. 

About the team

Stripe processes over $1T in payments volume per year, which is roughly 1% of the world’s GDP. The tremendous amount of data makes Stripe one of the best places to do machine learning. The Machine Learning Infrastructure (ML Infra) team builds services and tools that power every step in the ML lifecycle, including data exploration, feature generation, experimentation, training, deploying, serving ML models, and building LLM applications. With the phenomenal developments happening in the field of AI, we are positioned to accelerate the adoption of AI/ML across all parts of the company by building highly scalable and reliable foundational infrastructure. 

What you’ll do

You will work as the technical lead of the ML Infra space and a key contributor to the evolution of the platform that will substantially improve ML development velocity and MLOps maturity across the company. As a Staff Engineer, you’ll be empowered to make decisions with a large impact on Stripe. You will influence our investments and strategy while making our systems more reliable, secure, and a delight to use. You will work across functionally with other tech staff, data science, product, and senior leadership to land a bigger impact of ML at Stripe. We’re looking for people with strong technical leadership and background in building ML platforms. 

Responsibilities

  • Work with users and stakeholders directly to translate their needs to functional requirements. 
  • Define technical directions for projects with high ambiguity. 
  • Design the system architecture and solutions for the most challenging problems. 
  • Scope and lead large projects with significant business impact. 
  • Arbitrate critical decisions that balance completing priorities while meeting various constraints. 
  • Advise the leadership team on key technical considerations related to the end-to-end ML lifecycle at Stripe. 
  • Work effectively cross functionally and geographically dis tributed teams. 
  • Mentor and grow other engineers. Serve as a role model for designing, implementing, and operating great software systems. 

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. 

Minimum requirements

  • 10+ years of professional software development experience with a solid background on service oriented architecture and large-scale distributed systems
  • Track record of serving as a technical lead, with the ability to provide technical direction and mentor team members. 
  • Experience working on production ML platform services that powers hundreds to thousands of ML models.
  • Experience running operations for high availability and low latency systems.
  • Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
  • Demonstrated ability to work cross-functionally, collaborating effectively with ML engineers, data scientists, software engineers, product managers, and business stakeholders.

Preferred qualifications

  • Experience training and shipping machine learning models to production to solve critical business problems. 
  • Ability to synthesize ideas across the organization while setting a compelling technical vision.

Top Skills

Machine Learning

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