Quant Engineer – Nevermind Limited

About us
Nevermind Limited will develop and own proprietary systematic and AI-driven trading strategies. The programme will be absolute-return and multi-strategy, trading global futures, FX, equities and options through Interactive Brokers and other top-tier brokers. We are building a small, senior team in Jersey; you will be the engineering backbone of the strategy IP.

The role
You will design, build and own the research-to-production pipeline: data, backtesting, machine-learning models, execution connectivity and monitoring. You will work directly with the Head of Quant Strategies to take strategies live and keep them running, and you will have real ownership of the codebase rather than a slice of a large platform team.

What you will do
•      Build and maintain the strategy codebase in Python: signal research, feature pipelines, backtesting and portfolio construction

•      Research, train and validate ML and AI models for forecasting, regime detection and position sizing, with rigorous out-of-sample testing and overfitting controls

•      Own broker integration: Interactive Brokers API (TWS/IB Gateway) and other broker APIs for market data, order management and account reconciliation

•      Build the execution layer: order routing, fill handling, slippage and transaction-cost models, paper-to-live promotion

•      Set up and run market-data infrastructure: ingestion, storage, quality checks and corporate-action handling across futures, FX, equities and options

•      Implement monitoring, alerting and logging for live strategies, including risk-limit checks and automated kill-switches

•      Document the IP: strategy specs, model cards, experiment logs and reproducible research notebooks

Must-have
•      4+ years as a quant developer, quant researcher or ML engineer, with at least 2 years at a hedge fund, prop firm or systematic asset manager

•      Expert Python (pandas, NumPy, scikit-learn, PyTorch or TensorFlow) and comfort with the full stack: data engineering, modelling, deployment

•      Production experience with the Interactive Brokers API, and with at least one other broker or exchange API

•      Applied machine learning on financial time series, with a clear understanding of leakage, regime change and backtest overfitting

•      Working knowledge of futures, FX, equities and options: contract specs, rolls, margining, sessions and data quirks

•      Solid software engineering practice: Git, testing, CI, containerisation, Linux

•      Based in Jersey, or willing to relocate; eligible to obtain a Jersey work licence (Licensed status)

Preferred
•      Experience at a quantitative hedge fund building live systematic strategies

•      Exposure to multi-strategy or absolute-return portfolios (trend, carry, relative value, volatility)

•      QuantConnect/LEAN, Backtrader, Zipline or a comparable framework, and experience migrating strategies between frameworks

•      Experience with LLMs or generative-AI tooling in a research workflow

•      Cloud infrastructure (AWS, GCP or Azure), time-series databases, message queues

•      MSc or PhD in a quantitative discipline (mathematics, physics, computer science, statistics, financial engineering)

What we offer
•      Ownership of the codebase and the strategy pipeline from day one

•      [Base salary] plus a bonus linked to firm and strategy performance

•      Relocation support and assistance with the Jersey licence process

•      Budget for data, compute and tooling; a small team with short decision lines

How to apply
Send a CV and, if possible, a link to code or a short write-up of a strategy or model you took from research to live trading, to contact email below.

Please note there is no Application Link – please use email address.