Job Location: San Francisco, CA
Since we first opened our doors in 2009, the world of commerce has evolved immensely – and so has Square. After enabling anyone to make a payment and never miss a sale, we saw sellers stymied by disparate, outmoded products and tools that wouldn’t work together. So we expanded into software and started building integrated, omnichannel solutions – to help sellers sell online, manage inventory, run a busy kitchen, book appointments, engage loyal buyers, and hire and pay staff. And across it all, we’ve embedded financial services tools at the point of sale, so merchants can access a business loan and manage their cash flow all in one place.
Today, we’re a partner to sellers of all sizes – large, enterprise-scale businesses with complex commerce operations, sellers just starting out, as well as merchants who began selling with Square and have grown larger over time. As our sellers scale, so do our solutions. We all grow together.
There is a massive opportunity in front of us. We’re building a business that is big, meaningful, and lasting. And we are helping sellers around the world do the same.
The Fraud Machine Learning & Decision Science (MLDS) team within Square Risk is looking for a Machine Learning Tech Lead. This senior role will be responsible for driving machine learning technology strategy for Fraud at Square. This is a very visible role and touches on developing event-driven intelligent software across all money movement (and other events) across the entire Square seller ecosystem of products.
This touches on actively maximizing the trade-off of revenue growth and risk using artificial intelligence. The machine learning-driven software that we release interacts with every transaction and money movement within our seller ecosystem – a profound degree of scale and impact. Such machine learning techniques touch on reinforcement learning, decision theory, deep learning/representation learning, and optimization theory. In addition, we also strive to provide our sellers, through seller-facing products, with transparency around why our machine learning made a particular decision. This touches on algorithms in the relatively new space of explainable artificial intelligence.
This role will closely collaborate with product managers across the fraud vertical, Risk leaders, and other machine learning teams within the Risk Engineering and Machine Learning & Decision Science organization as well as ML teams across Square and Block. This also includes collaboration with various ML platform teams both within Risk across Block.
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Drive technical ML strategy across the Fraud vertical within Square Risk
Collaborate with and mentor other machine learning engineers in the team
Build machine learning/deep learning models that detect risk (e.g., fraud) activity in real-time across the Square seller ecosystem consisting of payments, banking, and other commerce enablement-related products.
Balance deeply technical concepts with creative “forward-thinking” growth principles to balance the tradeoff between risk and growth by looking holistically across the Square ecosystem.
Collaborate with business leaders, subject matter experts, and decision-makers to develop success criteria and optimize new products, features, policies, and models
An advanced degree (M.S., PhD.), preferably in Computer Science, Engineering, Statistics, Physics, Mathematics or a related technical field.
PhD with 4+ years (or Master 6+ years) industry working experience on applied Machine learning or Deep learning in a production environment with a history of delivering value to customers and the business.
A strong track record of performing modern machine learning model development using Python (numpy, pandas, tensorflow, pytorch, scikit-learn, etc.) within machine learning software development lifecycle paradigms.
Expert-level knowledge of modern techniques in machine learning and deep learning, e.g., transformer network architectures, with an orientation to maximizing such algorithms in a large-scale production setting. The reinforcement learning experience is a plus for developing optimal control policies
Familiarity with Linux/OS X command line, version control software (git), and general software development principles with a machine learning software development life-cycle orientation.
Machine learning strategic sequencing of methodological and software improvements to work back from maximizing core metrics associated with optimizing the business.
The ability to clearly communicate (verbal and written) complex results to technical and non-technical audiences and stakeholders (PMs, Operations, Engineers).
We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we’re doing to build a workplace that is fair and square? Check out our I+D page.
Additionally, we consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis.
We want you to be well and thrive. Our global benefits package includes:
- Healthcare coverage
- Retirement Plans
- Employee Stock Purchase Program
- Wellness perks
- Paid parental leave
- Paid time off
- Learning and Development resources
Block, Inc. (NYSE: SQ) is a global technology company with a focus on financial services. Made up of Square, Cash App, Spiral, TIDAL, and TBD, we build tools to help more people access the economy. Square helps sellers run and grow their businesses with its integrated ecosystem of commerce solutions, business software, and banking services. With Cash App, anyone can easily send, spend, or invest their money in stocks or Bitcoin. Spiral (formerly Square Crypto) builds and funds free, open-source Bitcoin projects. Artists use TIDAL to help them succeed as entrepreneurs and connect more deeply with fans. TBD is building an open developer platform to make it easier to access Bitcoin and other blockchain technologies without having to go through an institution.