Technology News, High Performance Computing

Bjarne Stroustrup, creator of the C++ programming language, has joined Susquehanna International Group (SIG)

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September 15, 2026 by Ivy Delaney

Bjarne Stroustrup, creator of the C++ programming language, has joined Susquehanna International Group (SIG) as a part-time Technical Fellow. This appointment establishes a direct link between the language’s originator and a major industry reliant on its capabilities; SIG intends for Stroustrup to help shape the optimisation and evolution of its systems. Elite C++ engineers are in high demand, with compensation exceeding $500,000 at firms like Susquehanna, where low-latency trading demands exceptional execution speed. Stroustrup previously spent eight years as a Managing Director and Technical Fellow at Morgan Stanley, suggesting a return to familiar territory.

Stroustrup’s Return to Finance: SIG and High-Frequency Trading

Susquehanna International Group (SIG) now employs engineers earning compensation exceeding $500,000, reflecting the economic value placed on optimizing C++ for high-frequency trading. Susquehanna is also demonstrating commitment to the broader C++ community through Platinum sponsorship of CppCon 2026, with Stroustrup scheduled to participate.

The continued dominance of C++ in high-frequency trading highlights its unique advantages in low-latency environments, where predictable performance and hardware control are paramount. According to eFinancialCareers, “Despite repeated predictions that newer languages will displace it, C++ remains difficult to replace wherever nanoseconds, memory layouts and hardware behaviour matter economically.” In this context, programming languages are not simply tools but integral components of trading strategies, and hiring the language’s originator signals a firm commitment to maximizing performance through meticulous code engineering.

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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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