Job Directory Postmates Machine Learning Engineer, Risk

Machine Learning Engineer, Risk Postmates
San Francisco, CA

Postmates is a company developing an urban logistics and on-demand delivery platform.

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About Postmates

Job Description

Postmates runs one of the largest marketplaces in the country, connecting consumers, merchants, and couriers in real-time. Building high powered intelligence atop our large-scale datasets is a serious challenge and we're looking for candidates who are ready to dig in. Postmates isn't just another ad platform or mobile app for delivering static content: We have real customers paying real money for a real service.

What does this team do?

Postmates enables hundreds of millions of dollars in local commerce every year. Our uniquely flexible platform facilitates the delivery of virtually anything from anywhere in over 60+ U.S. cities and we're set to expand both our transaction volume as well as geographic footprint even further. Safeguarding this success takes work and that's where the Postmates Risk Team comes in.

The Risk Team at Postmates builds systems to assess risk in real time and protect the platform from fraud. Our infrastructure aggregates, stores, and retrieves mission critical data. It supports statistical model creation and deployment. And it houses a real time graph database that provides a highly detailed picture of the entire Postmates ecosystem. Through the tools we build, the features we deploy, and the policies we put in place, we ensure the platform can continue to scale without succumbing to the threat of bad actors.

What will you do?

As a machine learning engineer on the risk team, you'll be the interface between our data scientists and the machine learning systems that empower them to assess risk in real-time across the platform . You'll be an active contributor to our shared ML model server technology by extending it, improving its performance, and allowing it to serve more model classes with better interfaces. You'll work closely with data scientists to assist with automation of model training and to build tools for understanding and tracking model performance . You'll develop highly scalable data pipelines to enable a fine-grained understanding of overall system performance. And you'll make sure the code is clean, beautiful, maintainable, and easy to work with--you won't just get the job done, you'll get it done with style.


* 3+ years of professional experience building and deploying large scale Machine Learning systems and models in production.
* A Bachelor's degree (or higher) in CS or equivalent knowledge and experience.
* You possess strong computer science fundamentals: data structures, algorithms, programming languages, distributed systems, and information retrieval.
* You have strong opinions about writing beautiful, maintainable, understandable code.
* You have strong information retrieval (SQL, etc) and manipulation (SQL, Pandas, etc) skills, and enjoy making complex information understandable.
* You have a curiosity about how things work.
* You are a strong communicator. Explaining complex technical concepts to product managers, support, and other engineers is no problem for you.
* You love it when things work, you understand that things break, and when things do fail, you dive in to determine the root causes and fix whatever's broken.

Bonus Points

* AWS development and operations experience
* Experience with the Apache Ecosystem - Kafka, Spark, Storm, Zookeeper, Etc
* A solid math and statistics background


* Competitive salary and generous stock option plan (stay aligned with the long term value you create)
* Medical, dental and vision insurance and it's 100% paid for by the company
* Tasty, healthy lunches
* Snack-filled kitchen (mostly healthy, but very tasty)
* Impact-first work environment (no politics, no pandering)
* Huge company vision (we need you to build the future, not just maintain the status quo)
* Awesome office in San Francisco close to mass transit

About Postmates

Postmates is a company developing an urban logistics and on-demand delivery platform.

5000 employees

201 3rd street

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