A rare chance to join one of the most technically sophisticated operators in onchain capital markets. Our client is a fast-growing crypto market maker and liquidity provider, built from the ground up by a founding team with elite pedigrees spanning tier-one HFT firms, top-tier hedge funds, and academia. The business is well-capitalised, growing rapidly, and operating at the cutting edge of both DeFi and centralised trading.
This is not a firm riding the crypto wave — it is a serious trading business with serious technology, providing institutional-grade liquidity, market data, and execution services across centralised and decentralised venues. For the right candidate, this represents an exceptional opportunity to do genuinely hard quantitative work in one of the most dynamic and under-researched corners of financial markets.
The firm's leadership holds advanced degrees from Oxford, Cambridge, and leading London universities, and the team has built and scaled trading systems at some of the world's most respected quantitative firms.
The Role
Our client is seeking a strong Quant Engineer to operate at the intersection of quantitative research and trading systems implementation. The successful candidate will take ownership of strategy development across DeFi and centralised venues — from initial research through to live deployment — working directly alongside the founding team.
This is a high-autonomy, high-impact position. The firm is small and moves quickly, meaning the successful candidate will have genuine influence over research direction and see their work in production from day one.
Candidates from firms such as Jump Trading, Wintermute, Tower Research, Jane Street, IMC, Optiver, Flow Traders, Keyrock, or similar quantitative trading and market making environments are strongly encouraged to apply.
Responsibilities
- Research, develop, and continuously improve quantitative strategies for DeFi liquidity provision, arbitrage, and execution across AMMs, DEX aggregators, perpetuals protocols, and RFQ venues
- Model onchain market microstructure — MEV exposure, gas dynamics, block timing, LP fee capture — and translate findings into production-ready signals
- Work closely with the engineering team to implement low-latency execution logic; own the full research-to-deployment loop
- Analyse tick-level market data, both onchain and off, to identify mispricings, liquidity patterns, and regime shifts
- Build and maintain rigorous backtesting and simulation frameworks that account for the real costs of onchain execution: slippage, gas, and revert risk
- Monitor live strategy performance, diagnose degradation, and iterate at pace
- Contribute to a broader data and analytics platform serving institutional clients
Candidate Profile
Essential
- Strong mathematical foundation — degree or higher in Mathematics, Physics, Statistics, or a related quantitative discipline
- Demonstrable experience in quantitative finance: strategy research, signal development, or systematic trading, with exposure to digital assets strongly preferred
- Strong Python skills applied to quantitative research, data analysis, and trading systems; comfort operating with large, complex datasets at scale
- Track record of contributing to trading systems end-to-end — from research and signal generation through to live execution
- Genuine, hands-on familiarity with DeFi protocols and onchain market dynamics
- Rigorous thinking around transaction costs, execution realities, and the gap between backtested and live performance
Advantageous
- Direct experience in DeFi: LP strategy, MEV, on-chain arbitrage, or protocol-level analysis
- Background in low-latency or HFT environments
- Proficiency in Rust or C++ for performance-critical work
- Knowledge of EVM internals, mempool dynamics, or cross-chain execution
- Experience with perpetuals, options, or structured DeFi products