About the job:
Square builds common business tools in unconventional ways so more people can start, run, and grow their businesses. When Square started, it was difficult and expensive (or just plain impossible) for some businesses to take credit cards. Square made credit card payments possible for all by turning a mobile phone into a credit card reader. Since then Square has been building an entire business toolkit of both hardware and software products including Square Capital, Square Terminal, Square Payroll, and more. We’re working to find new and better ways to help businesses succeed on their own terms—and we’re looking for people like you to help shape tomorrow at Square..
As a leader of machine learning engineers within the Risk Machine Learning team, you drive initiatives that enable a software and machine learning-centric view on all money movement and every transaction within the growing Square seller ecosystem. This touches on actively maximizing the trade-off of revenue growth and risk using artificial intelligence. The machine learning-first software that we build optimizes decisions against every transaction and money movement within our seller ecosystem – a profound degree of impact. Such machine learning techniques touch on reinforcement learning, decision theory, deep learning sequence modeling, and optimization theory.
- Strategically develop an operating thesis of the machine learning algorithm capabilities, software, and team against the goals of the organization. Specifically, how we can compound “reusable leverage” to guide a broader impact with “AI, first” software
- Partner closely with product managers, engineers, and organizational leadership to establish your team’s vision and roadmap by thoroughly understanding your customers’ needs
- Have an “owner and operator” mentality of evolving artificial intelligence driven products
- Build products, systems, and services that have immediate impact on our customers that are operated by machine learning, specifically modern deep learning architectures.
- Lead technical, design, and product discussions with other leaders across the organization and company and promote a machine learning development lifecycle culture within the team
- Relevant graduate degree or equivalent industry experience (5+ years preferred)
- Leadership experience exhibited by past experiences managing and growing teams in the machine learning environment creating growth in the evolution of products and metrics associated with team responsibilities
- Directly managed engineers for at least 2 years (including feedback, performance, hiring, and career guidance)
- Experience defining and driving toward a product roadmap for a production oriented data science and engineering team in a modern machine learning environment.
- Helping frame and chart a strategic directive and managing the execution and delivery of impactful solutions in the artificial intelligence space in a production setting.
- The ability to mentor and provide technical direction to a team of machine learning engineers and scientists while exhibiting both a technical and and product mindset.