Machine Learning Engineer (Modeling), Risk

Since we opened our doors in 2009, the world of commerce has evolved immensely, and so has Square. After enabling anyone to take payments 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, offer buy now, pay later functionality, book appointments, engage loyal buyers, and hire and pay staff. 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 in one place. Afterpay furthers our goal to provide omnichannel tools that unlock meaningful value and growth, enabling sellers to capture the next generation shopper, increase order sizes, and compete at a larger scale.

Today, we are a partner to sellers of all sizes – large, enterprise-scale businesses with complex operations, sellers just starting, as well as merchants who began selling with Square and have grown larger over time. As our sellers grow, so do our solutions. There is a massive opportunity in front of us. We’re building a significant, meaningful, and lasting business, and we are helping sellers worldwide do the same.

The Role

Block's Chargeback Risk Machine Learning team members build machine learning models and systems to precisely detect, intervene on, and reduce fraudulent activity across Block's Cash App and Square ecosystems. As part of our team, you and your work will safeguard the Cash App and Square ecosystems from financial loss and provide trustworthy and seamless financial experiences for millions of customers and sellers.

You Will

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  Partner with product, engineering, data science, policy, and operations to design and productionize ML-driven solutions to fight fraud at scale



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  Become a risk domain expert and expert to lead strategy and planning on your workstreams.



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  Develop tooling and processes to improve the effectiveness and speed of the ML development lifecycle



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  Investigate and use state-of-the-art modeling algorithms and third-party data sources to boost model performance



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  Contribute positively to our team culture as a collaborative, empathetic, and reliable teammate.

You Have

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  3+ years of machine learning experience



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  A degree (preferably graduate level) in Computer Science, Engineering, Statistics, Physics, Applied Math or a related technical field



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  Hands-on experience independently designing, deploying, and troubleshooting ML solutions using methods such as tree-based models, deep learning, transfer learning, or reinforcement learning.



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  Proficiency in modern ML stacks such as: PySpark, PyTorch, MLflow, GCP Vertex AI, Workflow orchestration tools (i.e. Airflow, Prefect)



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  Proficiency with containerization, cloud platforms (AWS, GCP), and CI/CD practices.



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  Experience collaborating with cross-functional teams to prioritize, scope, and deploy ML/AI solutions at scale



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  Experience helping your teammates grow through mentorship and providing constructive feedback.



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  A natural sense of curiosity, and experience with Block's mission of economic empowerment.