Quantitative trading firm Hudson River Trading (HRT) has selected AI cloud Lambda to provide AI compute for its model training and trading simulation workloads.
Under the agreement, Lambda will provide HRT with access to Nvidia HGX B200 systems, along with advanced networking, storage, and orchestration.
HRT turned to Lambda after its own compute needs began growing, and the trading firm needed rapid access to compute with high uptime.
“Lambda stood out for its technical depth and operational clarity,” said Gerard Bernabeu Altayo, compute systems lead at HRT. “We’re confident we’ve found the right partner to help power our workloads.”
“HRT is exactly the kind of customer Lambda was built for: researchers who need massive amounts of compute and infrastructure that delivers,” said Stephen Balaban, co-founder and CTO of Lambda. “We’re proud to power HRT’s research, and we’re here to make sure they have everything they need to do their best work.”
Algorithmic or quantitative trading is a type of “high frequency trading” that relies on speed and latency as part of its strategy. Earlier this year, a fellow quantitative trading firm, Jane Street, signed on to secure $6 billion in AI cloud capacity from Lambda competitor, CoreWeave.
So far in May, Lambda has secured a $1 billion syndicated senior secured credit facility and reshuffled its leadership team, appointing Michel Combes as CEO, while co-founder and former CEO Stephen Balaban is stepping into the role of CTO.