Quantitative Researcher

LQT Technologies Limited

Offer of Employment

Position: Quantitative Researcher - Systematic Trading (HFT)

Location: London (UK) - hybrid

Experience: 0-5 years (new grad or early-career welcome)

Employment type: Permanent, full-time

About LQT

Founded in late 2024, LQT Technologies is a deliberately small, high-performance team building fully systematic trading strategies for global markets. We combine rigorous mathematics with modern engineering on a HPC grid spanning tens of thousands of CPUs & GPUs, then deploy our algorithms and support their operations. Collaboration, open information-sharing and a meritocratic culture drive everything we do.

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.

• Frictionless idea → P&L: Thin wall between research and production; prototypes graduate fast to realistic sims and live trading
• Everyone on the team contributes across math, data, and code: no rigid silos; 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

• 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

Everyone on the team shares two traits: learns fast and has a strong drive. Beyond those for the quantitative researchers among the team we want

• 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

• High proficiency in C++
• Practical experience in reinforcement learning and advanced deep learning
• Cuda, SIMD knowledge
• Containers proficiency

• 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
• Flat, meritocratic and transparent culture: Decisions are fast and good ideas win, regardless of tenure
• Competitive pay with uncapped performance bonus

The process is short but intense

1. Introductory call
2. Technical screen
3. On-site: technical & culture conversations and pair-research exercises

Ready to push technical boundaries with us?

Email with your CV. We review every application personally and respond quickly.