Software Engineer Machine Learning Infrastructure

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

The Machine Learning Infrastructure group at Stripe aims to provide
state of the art infrastructure and support for building and
operationalizing AI/ML models for all business verticals within the
company, including but not limited to models that mitigate risks across
Stripe's products and services globally, and models that help our
customers to fight fraud by leveraging Stripe's user facing products
like Radar and Identity. ML is a top priority for Stripe in the coming
years. 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 platform infrastructure teams to build the powerful, flexible, and
user-friendly systems that substantially increase ML-Ops velocity
across the company.
Responsibilities

• Building powerful, flexible, and user-friendly infrastructure that
  powers all of ML at Stripe.
• Designing and building fast, reliable services for ML model training
  and serving, and scaling that infrastructure across multiple regions.
• Creating services and libraries that enable ML engineers at Stripe to
  seamlessly transition from experimentation to production across
  Stripe's systems.
• Pairing with product teams and ML engineers to develop easy-to-use
  infrastructure for production ML models.

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. Many of our engineers work remotely from both the US and
Canada, and we'd be happy to talk to you about the possibility of
working remotely.

It's not expected that any single candidate would have expertise across
all of these areas. For instance, we have wonderful team members who are
really focused on their customers' needs and building amazing user
experiences, but didn't come in with as much systems knowledge.
Minimum requirements

• Over five years of experience building software applications in large
  scale distributed systems.
• A strong sense of curiosity and a desire to both learn and share
  knowledge with your peers. We like to work in a collaborative
  environment and hope you do too.
• A solid engineering background and experience with infrastructure
  and/or distributed systems. You'll work mostly in Python and Java but
  we care more about your general engineering skills than your knowledge
  of a specific language.
• Familiarity with the full life cycle of software development, from
  design and implementation to testing and deployment.
• Experience with building and maintaining high availability, low
  latency systems, especially with respect to reliability, testing, and
  observability.
• A sense of pragmatism: you know when to aim for the ideal solution and
  when to adjust course.

Preferred qualifications

• Over 2 years of experience supporting Machine Learning Infrastructure.
• Experience optimizing the end-to-end performance of distributed
  systems.
• Experience training and shipping machine learning models to production
  to solve critical business problems.

Pay and Benefits

The annual US base salary range for this role is $157,100 - $212,500. For sales roles, the range provided is the role's On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate's experience, qualifications, and location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process.

Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.