Lead Machine Learning Engineer, Risk AI

Posted 6 Days Ago
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Melbourne, Victoria
Hybrid
7+ Years Experience
Blockchain • Fintech • Mobile • Payments • Software • Financial Services
We want to make the world’s relationship with money more relatable, instantly available, and universally accessible.
The Role
The Lead Machine Learning Engineer will design and maintain ML systems to detect fraud in real-time, collaborate with teams globally, and lead experiments to validate new ideas while applying advancements in technology to enhance existing products and systems.
Summary Generated by Built In

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 ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 50+ million monthly active customers. We want to redefine the world's relationship with money to make it more relatable, instantly available, and universally accessible.
Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We've been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.
The Role
The Risk AI team's mission is to develop cutting-edge deep learning-based signals and learned representations for Risk ML models. Our focus is on exploring, developing, and implementing state-of-the-art (SOTA) alternatives to traditional feature-based machine learning methods. By leveraging the latest advancements in AI, we aim to enhance real-time evaluation pipelines used by the Risk ML team to detect and prevent fraudulent transactions and activities. Cash App holds people's money, and maintaining customers' trust is absolutely essential to our brand. Preventing scams and fraud is a major component of building that trust. The Risk AI team is at the forefront of this effort, utilizing SOTA approaches to drive innovation and protect our users from emerging threats.
You will:

  • Design, build and maintain Machine Learning systems that enable us to flag fraudulent activities in real-time
  • 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 colleagues located across the globe
  • Own your solutions from design through to operation: we all share the pager!
  • Lead the conception, design, and implementation of large-scale experiments to validate novel ideas rapidly and comprehensively
  • Apply the latest theoretical advancements to enhance existing products, processes, and technologies, ensuring they remain at the forefront of the industry
  • Engage in the creation of experiments, prototyping, and architectural design, contributing to a diverse range of computer science domains such as machine learning, data mining, natural language processing, and performance analysis
  • Take the lead in designing systems, data structures, frameworks, and evaluation metrics for research solution development
  • Conduct experiments aligned with research inquiries, employing simulations and prototypes to assess the outcomes


You have:

  • ~8 years of Software Engineering + some professional ML experience
  • A track record of solving business problems with technology and proven experience successfully taking ownership of an end-to-end solution
  • Have lead complex, multi person projects
  • Work autonomously in a fast paced, ambiguous and unpredictable environment
  • Be naturally curious & eager to learn
  • Work creatively, taking initiative and leading when required
  • Grow your solutions, maintaining and fixing them as necessary
  • Communicate via clear and concise writing to facilitate asynchronous collaboration across multiple time zones
  • Reason about complex, distributed systems at high scale
  • Proficiency in machine learning techniques, experimental design and data engineering
  • Strong programming skills in languages such as Python, TensorFlow, or PyTorch.


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.

Top Skills

Python
The Company
Melbourne, Victoria
3,500 Employees
Hybrid Workplace
Year Founded: 2013

What We Do

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.

Why Work With Us

At Cash App, our mission is simple yet ambitious: to redefine the world’s relationship with money by making it more relatable, instantly available, and universally accessible. To make this real, we’re building a team of dreamers, innovators, and risk-takers to break the mold of what a financial brand can be. If that’s you, then come join us.

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Cash App Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Cash App has always been a distributed team working across timezones and continents. Today, we're remote-first by default, but encourage you to choose how you want to work: from home, one of our offices, or a mix of both.

Typical time on-site: Flexible
Melbourne, Victoria
Sydney, New South Wales

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