Who are we?
FalconX is the most advanced digital asset platform for institutions. We provide trade execution, credit & treasury management, prime offering and market making services. Given our global operations, industry-leading technology and deep liquidity, we have facilitated client transactions of $1 trillion in volume. Our products & services are regulated, compliant and trusted.
We are a team of engineers, product builders, institutional sales and trading leaders, operations experts, and business strategists. Our teammates have entrepreneurial experience and come from companies such as Google, Apple, Paypal, Citadel, Bridgewater, and Goldman Sachs. And, we embody our values: Think big; Drive bold outcomes; Be one team; Iterate with speed; and be an entrepreneur.
We prioritize learning. Outcomes are mission-critical, but we also believe that learning in success and in failure will drive our continued success. Our industry is emergent - there’s no shortage of experiments to get involved with and to continue growing and learning together.
Impact :
At FalconX, you’ll help create a more open financial system. In building trading, credit and custody infrastructure, we are enabling thousands more institutions to enter the market and support a more open and accessible financial system. The world’s largest financial institutions from Wall Street to Silicon Valley will turn to you for products that provide unparalleled seamless, efficient and secure access to the cryptocurrency sector.
FalconX is hiring a Machine Learning Engineer focused on our core platform stack to help introduce a new, in-demand product line for the company that integrates seamlessly with our proprietary, best-in-class Prime Brokerage platform. We are looking for an experienced Software Engineer with a background in building scalable, distributed systems as well as a strong understanding of blockchain, wallets, and platforms to build upon our vision of an open financial system.
Responsibilities:
Qualifications:
Understand the required skills and qualifications, anticipate the questions you may be asked, and study well-prepared answers using our sample responses.
Machine Learning Engineer Q&A's