Algorithm Engineer, ‘Tectonic’ Trading
The firm was founded by engineers and retains its original code-first ethos by hiring technically minded individuals who like solving complex technical puzzles and being handsomely paid for it. As well as from top tier quant firms, personnel has come from DeepMind, OpenAI, NVIDIA. Their aim was to differentiate themselves from certain investor/trader-driven competitors where domineering investment professionals run the roost and engineers are a support function, and rework the narrative so that the engineers are the impact makers.
They trade Systematic Equities in Europe, Asia and North America and their returns have been astonishing. They have done so through leveraging advanced Deep Learning and NLP techniques, finding ‘alpha’ in alternative datasets that competitors haven’t even thought to source, and building beautifully clean research and data infrastructure.
They are now expanding into Systematic Futures. They have acquired research personnel to move the dial but are seeking Quant (Research) Engineers who can help build simulation/backtesting infrastructure and write software to implement strategies seamlessly.
Required background:
- Their stack is C++/Python. Genuine expertise in at least one of these is vital.
- Any experience building extremely data-intensive platforms, very low level ecosystems or intricate ML infra is very interesting to them.
- Computer Science or Electrical Engineering background, top institution. You’ll need CompSci fundamentals to build the quality of software necessary. MS and PhD are particularly interesting, provided combined with commercial experience.
- Red hot communication to be able to collaborate effectively with ML scientists and Quant Researchers.
- Experience in quant finance nice to have, but by no means necessary.
Pre-Application:
- Please do not apply if you're looking for a contract or remote work.
- You must be eligible to live and work in the US, without requiring sponsorship.
- Please ensure you meet the required experience section prior to applying.
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