Company Description
It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic app, bringing a better way to send, spend, invest, borrow and save to our millions of monthly active users. With a mission to redefine the world's relationship with money by making it more relatable, instantly available and universally accessible, at Cash App you'll have the opportunity to make a real-world impact with your career.
Today, Cash App has thousands of employees around the world with a culture geared toward creativity, collaboration and impact. We've been a distributed team since day one, and continue to value working across time zones and continents both remotely and in our Cash App offices.
Our offices are great, but many of our roles can be done remotely from the countries where Block operates. We tailor our experience to champion our employees' creativity and productivity wherever they are.
Check out our locations, benefits and more at cash.app/careers.
Job Description
We're looking for a machine learning engineer to join Cash App's ML Feature Systems team, which builds cutting edge machine learning infrastructure to redefine the world's relationship with money. Cash ML uses our large and unique datasets to model, understand, and predict customer behaviour to help optimise customer acquisition, engagement, retention, personalisation, and more.
You'll have the chance to work across the complete machine learning lifecycle, focusing more specifically on feature extraction, storage and pipelines. We are looking for someone who is hungry to create the development of large machine learning systems alongside talented modelers and engineers, as well as a strong architect who can create simple, reusable abstractions for performing complex machine learning tasks.
What you'll do:

• Design, build and maintain Machine Learning systems that power Cash's ML Feature Systems stack
• Work hand-in-hand with ML Modellers to identify and integrate new data sources, heuristics and models
• Solve challenging technical problems at scale, collaborating with folks located here in Australia and across the globe
• Own your solutions from design through to operation: we are all on the pager!

Qualifications
Prior experience or knowledge in Machine Learning is helpful but definitely not a prerequisite: if you are a solid software engineer then we are happy to train you up in the mysterious ways of ML!
We're expecting you to have at least 2 years of industry experience, with a track record or desire to:

• Work autonomously in a fast paced, ambiguous and unpredictable environment
• Be naturally curious & eager to learn
• Work creatively, taking the initiative and leading when required
• Grow your solutions, fixing them as necessary
• Communicate via clear and concise writing to facilitate collaboration across multiple time zones
• Reason about complex, distributed systems at high scale within a mixed ecosystem of sync, async, RPC and event-driven architectures

Qualifications
Prior experience or knowledge in Machine Learning is helpful but definitely not a prerequisite: if you are a solid software engineer then we are happy to train you up in the mysterious ways of ML!
We're expecting you to have at least 2 years of industry experience, with a track record or desire to:

• Work autonomously in a fast paced, ambiguous and unpredictable environment
• Be naturally curious & eager to learn
• Work creatively, taking the initiative and leading when required
• Grow your solutions, fixing them as necessary
• Communicate via clear and concise writing to facilitate collaboration across multiple time zones
• Reason about complex, distributed systems at high scale within a mixed ecosystem of sync, async, RPC and event-driven architectures