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
Stripe’s mission is to build the economic infrastructure for the internet. Risk Engineering brings together machine learning with product development to lower Stripe’s financial and regulatory risk at scale, while retaining a best in class user experience.
We build ML and backend systems to catch fraudsters, understand users’ cash flow and financial health, and ensure Stripe’s users are compliant with regulatory and financial partner requirements.
We protect Stripe’s brand while also protecting the company from financial losses that can put Stripe’s business at risk.
The Risk group consists of machine learning, backend, and full stack engineers who tackle this problem through creative new product ideas and impactful machine learning models.
We are undertaking several new efforts, where you can have an outsized impact on the architecture, implementation, and design choices behind these systems.
What you’ll do
Responsibilities
- Designing, training, improving & launching models
- Proposing and implementing ideas that directly reduce Stripe’s financial losses
- Building systems that evaluate businesses for risk and take appropriate actions
- Working with our partner teams to launch new policies that directly impact Stripe’s bottom line
- Helping engineers across the company to develop technologies for scaling our infrastructure
- Debugging production issues across services and multiple levels of the stack
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
- Have at least 2 years of industry experience in training ML models
- Enjoy and have experience shipping ML models in a large-scale production environment
- Hold yourself and others to a high bar when working with production systems
- Take pride in taking ownership and driving projects to business impact
- Thrive in a collaborative environment
Preferred qualifications
Have experience in Python, Scala (Spark), or Ruby
Hybrid work at Stripe
This role is available either in an office or a remote location (typically, 35+ miles or 56+ km from a Stripe office).
Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams.
A remote location, in most cases, is defined as being 35 miles (56 kilometers) or more from one of our offices. While you would be welcome to come into the office for team / business meetings, on-sites, meet-ups, and events, our expectation is you would regularly work from home rather than a Stripe office.
Stripe does not cover the cost of relocating to a remote location. We encourage you to apply for roles that match the location where you currently or plan to live.
Pay and benefits
The annual US base salary range for this role is $192,000 - $288,000. 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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