量化开发

Introducing CrushAI, a Smart AI Agent Protocol in development since Jan 2024. Incubated by the Nvidia Inception program, they are building the most efficient trading platform with advanced market intelligence, powered by AI Agents. Crush will deploy a network of AI Agents, each specialised for a unique function within crypto. One of the first set of Agents we are deploying will power our own trading platform, monitoring the market, gathering advanced market intelligence and enabling never-before-possible automated trading strategies like news-based and sentiment-based trading strategies for our users. Crush will also deploy other AI agents that exists in game worlds as companions and NPCs, and even Dapps that interact with various decentralised applications and beyond.

关于 Crush / About Crush Crush 是一个 零代码 AI 量化交易平台，用户可通过自然语言创建并执行跨资产自动化交易策略。 我们将 AI Agent 与 量化逻辑引擎 相结合，实时交易社交、新闻与市场信号。 Crush is a no-code AI trading platform that allows users to build and execute multi-asset automated strategies using natural language. We combine AI Agents with quantitative logic engines to trade across social, news, and market signals in real time. 我们正在寻找一位 量化系统开发工程师，独立负责开发 回测与重放引擎、实时信号计算模块、量化监控分析系统，并基于系统结果 研究与验证可盈利的量化策略。 We’re seeking a Quant Systems Developer to independently lead the development of the Backtesting & Replay Engine, Real-time Signal Computation Module, Quantitative Monitoring & Analytics System, and develop profitable quant trading strategies based on these systems.

主要职责 / Key Responsibilities 1. 回测与重放引擎开发 / Backtesting & Replay Engine • 构建事件驱动的量化回测框架，支持 Tick 与 K 线级别重放。 • 模拟真实交易行为（下单、滑点、延迟、盈亏跟踪）。 • 输出策略绩效指标（收益率、回撤、Sharpe、胜率等）。 • Build an event-driven backtesting framework supporting tick and bar-level replay. • Simulate realistic trading behavior (order fills, slippage, latency, PnL tracking). • Output detailed strategy performance metrics (return, drawdown, Sharpe, win rate, etc.). 2. 实时信号与指标计算模块 / Real-time Signal & Indicator Engine • 开发高性能指标计算引擎（RSI、EMA、MACD、ATR、VWAP、布林带等）。 • 为上层 DSL 与 AI Agent 提供标准化接口（REST/WebSocket）。 • 维护时间序列数据管线与缓存系统（ClickHouse 优先）。 • Develop a high-performance indicator computation engine (RSI, EMA, MACD, ATR, VWAP, Bollinger, etc.). • Provide standardized APIs (REST/WebSocket) for DSL and AI agents. • Maintain efficient time-series data pipelines and caching 3. 量化监控与分析系统 / Quant Monitoring & Analytics Dashboard • 搭建策略状态、信号监控与绩效分析可视化系统。 • 实现 PnL、持仓、风险暴露等数据可视化与图表展示。 • 优化数据查询与展示性能。 • Build visualization interfaces for strategy states, signal monitoring, and performance analytics. • Display PnL, exposure, and risk metrics in real time. • Optimize query performance and data delivery for high-frequency visualization. 4. 量化策略研究与验证 / Strategy Research & Validation • 基于所构建的系统，研究、开发并验证可盈利的量化交易策略。 • 分析不同指标组合、参数与触发条件对策略表现的影响。 • 提供回测结果与收益分析报告，用于模型优化。 • Research, design, and validate profitable trading strategies using the developed systems. • Analyze how different indicators, conditions, and parameters impact performance. • Produce backtest results and performance analytics to support model refinement.

Salary: Competitive 薪资待遇： 具竞争力，面议