Software Engineer, Machine Learning Infrastructure

Posted 16 Hours Ago
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Toronto, ON, CAN
In-Office
Junior
Payments • Software
The Role
Build scalable, reliable ML infrastructure and services for notebooks, training, experimentation, deployment, serving, and LLM applications. Partner with ML engineers and product teams to enable production-ready MLOps workflows, improve developer productivity, and operate high-availability, low-latency systems across regions.
Summary Generated by Built In
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 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 closely with machine learning engineers, data scientists, and product engineering teams to enable seamless end-to-end experience in building solutions across data, analytics, and AI/ML platforms. You will build the next generation of ML Infra services and major new capabilities that substantially improve ML development velocity and MLOps maturity across the company.

Responsibilities 
  • Designing and building scalable, reliable, and secure services for notebooks, ML model training, experimentation, serving, and LLM applications across multiple regions. 
  • Creating services and libraries that enable ML engineers at Stripe to seamlessly transition from experimentation to production across Stripe’s systems. 
  • Working directly with product teams and ML engineers to improve their day-to-day productivity. 
  • Taking ownership of and finding solutions for technical and product challenges by working with a diverse set of systems, processes, and technologies.
Who you are

We’re looking for people with a strong background or interest in building successful products or systems; you’re passionate about solving business problems and making impact, you are comfortable in dealing with lots of moving pieces; and you’re comfortable learning new technologies and systems. You are comfortable working with other Stripe teams across the US and Canada.

Minimum requirements
  • 2+ years of professional software development experience with a solid background on service oriented architecture and large-scale distributed systems
  • Experience working through the full life cycle of software development, from talking to users, to design and implementation, to testing and deployment, to operations
  • Experience working on production ML platforms, MLOps solutions, or building LLM applications
  • Experience running operations for high availability, low latency systems
  • Experience partnering with other teams to drive business outcomes
  • A sense of pragmatism: you know when to aim for the ideal solution and when to adjust course
Preferred qualifications 
  • Experience building and shipping production AI agents
  • Familiarity with the LLMs and LLM Frameworks
  • Experience training and shipping machine learning models to production to solve critical business problems

Skills Required

  • 2+ years of professional software development experience
  • Solid background in service-oriented architecture and large-scale distributed systems
  • Experience across full software lifecycle: user research, design, implementation, testing, deployment, operations
  • Experience working on production ML platforms, MLOps solutions, or building LLM applications
  • Experience running operations for high availability, low latency systems
  • Experience partnering with other teams to drive business outcomes
  • Pragmatism: know when to aim for ideal solution vs adjust course
  • Experience building and shipping production AI agents
  • Familiarity with LLMs and LLM frameworks
  • Experience training and shipping machine learning models to production

Stripe Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Stripe and has not been reviewed or approved by Stripe.

  • Healthcare Strength Healthcare is positioned as comprehensive across mental, physical, and medical plans. Mental-health support is repeatedly surfaced as a meaningful part of overall coverage.
  • Parental & Family Support Parental leave and fertility benefits are highlighted as core elements of the package. Leave-related benefits are portrayed as a standout area of support for families.
  • Fair & Transparent Compensation Compensation is framed as a relative strength compared to other parts of the employee experience. Pay is frequently characterized as competitive and, for many roles, perceived as fair in absolute terms.

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The Company
HQ: San Francisco, CA
5,360 Employees
Year Founded: 2010

What We Do

Stripe is a technology company that builds economic infrastructure for the internet. Businesses of every size—from new startups to public companies like Salesforce and Facebook—use the company’s software to accept online payments and run technically sophisticated financial operations in more than 100 countries. Stripe helps new companies get started and grow their revenues, and established businesses accelerate into new markets and launch new business models. Over the long term, Stripe aims to increase the GDP of the internet.

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