Machine Learning Engineering Manager, Payment Intelligence

  • Stripe
  • Seattle, WA, USA
  • Sep 10, 2019
Full time Engineering

Job Description

The Payment Intelligence group is responsible for optimizing each of the billions of dollars of transactions processed by Stripe each year on behalf of our users, in order to maximize successful transactions while minimizing payment costs and fraud. We own products like Radar from end to end and work across the technical stack: from machine learning over our users’ data, to integrating ML intelligence and serving real-time predictions as part of Stripe’s payment infrastructure, to building user-facing product surfaces like dashboards and controls.

You will:

-Work with a team of talented engineers to optimize transactions on behalf of our payment users.-Drive the roadmap and priorities for your team, and work with dependencies across the company.-Be deeply involved in building and improving machine learning models to optimize payment flows.-Support the engineering team in achieving a high level of technical excellence and stability.-Manage processes to help the team do its best work and interface effectively with the rest of Stripe.-Recruit, coach and develop engineers.-Contribute to engineering-wide initiatives as a member of Stripe’s engineering management team.

You may be a fit for this role if:

-You’ve managed teams that owned and operated critical machine learning models in production. Your team has significant responsibility over the funds flowing through Stripe, and the ability to make or break Stripe’s future.-You enjoy learning and diving into the nuts-and-bolts of ML models as well as integrating, operating, and evaluating the models in a production environment.-You work very well cross-functionally, and are able to think rigorously and make hard decisions and tradeoffs.-You thrive on a high level of autonomy and responsibility.-You encourage a healthy work environment that’s both supportive and challenging.-You’re technical enough to ask engineers good questions about architecture and product decisions, and have domain expertise in machine learning.-You have at least two years of engineering management experience.

What’s it like to work at Stripe?

Stripe is helping the internet fulfill its potential as a platform for economic progress by building software tools that accelerate global economic access and technological development. Stripe makes it easy to start, run and scale an internet business from anywhere in the world.

Stripe is, at its heart, an engineering company. To provide a missing pillar of core internet infrastructure, we hire people with a broad set of technical skills (and from a wide variety of backgrounds) who are ready to take on some of the most challenging problems in the industry – from reliably handling 100M API requests per day, to building adaptive machine learning as a result of years of data science and infrastructure work, and enabling entrepreneurs worldwide to start a global internet business.

We look at Stripe as a constant work in progress and the same is true of our people; for all of us, we believe the best is yet to come. We’re here to support each other in our curiosity and creativity – which we pursue through thoughtful discussion and knowledge-sharing among a diverse set of peers and colleagues.

We encourage all engineers to transition teams once every year and a half and also take on short-term projects with other teams across Stripe. This enables engineers to learn how different parts of Stripe work while also establishing stronger ties and cross-pollination between groups.

We contribute to existing open-source projects and the people working on them, and we release several tools as open-source.

We want to work in a company of warm, inclusive people who treat their colleagues exceptionally well. The kind of people who are committed to going out of their way to help other Stripes in the short-term and pushing them to improve over the long-term (by helping them to get better at what they do).We’re a highly cross-functional organization and view that as part of the fun: we design our space to encourage as much collaboration as possible. We have long tables in the kitchen for a reason (to enable everyone to meet new people and learn from them). We also have a culture of transparency that we carry through to email communication, ensuring that Stripes all around the world have the information they need to make good local decisions.

In both our products and our people, we aim to reflect, represent and advocate for all of our users, globally. Our users transcend geography, culture and language; what we share, collectively, is a drive to create a fairer, more economically interconnected world.