LQT Technologies
Quantitative Researcher
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ABOUT THE ROLE
As a Quantitative Researcher you'll work side-by-side with quantitative developers and own the path from hypothesis to live P&L. There is effectively zero red tape between research and engineering - if you want to test a new signal in the morning with an experiment, and benchmark AVX256 vs AVX512 instructions in the afternoon, we'll hand you the keys.
WHAT MAKES THIS ROLE DIFFERENT
- Frictionless idea → P&L: Thin wall between research and production; prototypes graduate fast to realistic sims and live trading.
- No rigid silos: Everyone on the team contributes across math, data, and code; shared ownership of results.
- Modern by default: Kubernetes, Python + uv, Arrow/Parquet, C++23; reproducible, containerized, observable.
- Real hardware: HPC grid with tens of thousands of SOTA CPUs and GPUs.
WHAT YOU'LL DO
- Work on predictive models: Explore large/heterogeneous datasets, come up with new ideas and test them.
- Run simulations: Design experiments to test hypotheses, code those and run them on the HPC grid.
- Work on productionization: Translate your research ideas into clean, production-ready code and partner with others on execution, monitoring, and alerting.
- Make it last: Implement automated sanity checks, drift detection, and anomaly investigation - garbage in, garbage out, we want some well-thought-out guardrails.
- Research platform: Contribute to shared tooling that makes great research reproducible and fast. If you see areas of improvement, you’ll have the opportunity to suggest changes and even tackle them.
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WHAT WE'RE LOOKING FOR
Everyone on the team shares two traits: learns fast and has a strong drive. Beyond those, we look for:
- Deep understanding of probability, statistics, and linear algebra. Ability to absorb PhD-level concepts fast.
- Feel for ML and AI methods. Intuition and curiosity.
- Solid grasp of algorithms, data structures, and performance optimization.
- Strong Python for research; good engineering habits (tests, code review, CI). You have to be able to read C++ at the very least.
- Comfort with Linux/Unix, Git, and command-line tooling; containers proficiency is a plus.
- Experience writing unit/integration tests and using CI systems.
- Clear, concise communication and a bias toward action.
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BONUS POINTS FOR
- High proficiency in C++
- Practical experience in reinforcement learning and advanced deep learning
- Cuda, SIMD knowledge
- Containers proficiency
WHY JOIN US
- High exposure with accountability: Take ideas from the whiteboard to live P&L.
- Serious firepower: Immediate access to an HPC grid with massive CPU/GPU capacity and plenty of data.
- Meritocratic culture: Flat, meritocratic and transparent culture: Decisions are fast and good ideas win, regardless of tenure.
- Compensation: Competitive pay with uncapped performance bonus.
INTERVIEW PROCESS
The process is short but intense:
- Introductory Call
- Technical Screen
- On-Site SessionTechnical/culture talks & pair-research
HOW TO APPLY
Email us with your CV. Ready to push technical boundaries with us? We review every application personally and respond quickly.
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