Staff Machine Learning Infrastructure Engineer (Technical Leader)
Stripe
Reading Station, PA
machine learning
learning
infrastructure
engineer
technical
stripe
infrastructure
machine learning
learning
engineering
sales
production
technical
February 16, 2023
Stripe
Reading Station, PA
FULL_TIME
Who we are
About 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 organization provides infrastructure
and support to run machine learning workflows and ship to production,
tooling and operational capacity to accelerate the use of these
workflows, and opinionated technical guidance to guide our users onto
successful paths.
What you'll do
You willwork 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
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
Pay & Benefits
The annual US base salary range for this role is $240,600 - $339,700. 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.
About 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 organization provides infrastructure
and support to run machine learning workflows and ship to production,
tooling and operational capacity to accelerate the use of these
workflows, and opinionated technical guidance to guide our users onto
successful paths.
What you'll do
You willwork 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
- Create long term technical vision for the org, and identify paths to
deliver value in shorter term phases - Lead the 0-1 delivery of powerful, flexible, and user-friendly
infrastructure that powers all of ML at Stripe - Designing and building fast, reliable services for ML feature
engineering, model training and model serving, and scaling that
infrastructure across multiple regions - As a leader within Engineering, assist with team growth and
development while maintaining a high bar for excellence and and
technical curiosity - Create services and libraries that enable ML engineers at Stripe to
seamlessly transition from experimentation to production across
Stripe's systems - Own and build cross-functional partnerships with stakeholders
including dependency engineering teams, product, design,
infrastructure, and operations
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
- Minimum of 15+ years of engineering experience OR equivalent combined
work experience reflecting domain expertise as relevant to this
position - Demonstrated experience of leading company-wide initiatives spanning
multiple teams and organizations OR leveraging deep domain expertise
to influence tech roadmap planning and execution - Demonstrated ability to effectively collaborate across multiple teams
and stakeholders to drive business outcomes - Demonstrated ability to balance execution and velocity with security,
reliability, and efficiency - Experience, mentoring, and investing in the development engineers and
peers
- Experience optimizing the end-to-end performance of distributed
systems. - Experience designing and implementing data processing systems using
the lambda architecture . - Experience debugging and optimizing large scale data pipelines using
Apache Spark. - Experience training and shipping machine learning models to production
to solve critical business problems.
Pay & Benefits
The annual US base salary range for this role is $240,600 - $339,700. 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.
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