Algorithm Engineer

Retu Management Consulting Limited; Hong Kong; Presencial; HKD 900.000 - 1.300.000; Jornada completa

Descripción de la vacante

Retu Management Consulting Limited in Hong Kong is seeking a quantitative researcher to join its AI-native alpha research team. The role focuses on translating academic literature into executable backtests and developing high-capacity signals.

You will work with transformers, GNNs, time-series models and implement rigorous anti-overfitting, cross-validation, and code auditing to ensure accurate PnL attribution and robust research outputs.

Formación

• Master’s or Ph.D. in CS, math, physics, statistics or financial engineering.
• Strong AI-native competency and prompt engineering.
• Solid grounding in probability theory, linear algebra, time-series forecasting.
• Self-driven, detail-oriented, collaborative researcher mindset.

Responsabilidades

• AI-driven alpha discovery from literature to backtests.
• Feature engineering and modeling with Transformers, GNNs, time-series models.
• Workflow automation with LLMs and AI agents for hyperparameter tuning and PnL attribution.
• Architecture and code auditing for efficiency and bias prevention.

Conocimientos

AI development tools

Prompt engineering

Probability & statistics

Time-series forecasting

Educación

Master’s or Ph.D. in Computer Science, Mathematics, Physics, Statistics, or Financial Engineering

Herramientas

RAG architectures

LLMs

Autonomous AI agents

Descripción del empleo

Job Description:

About the Role & Team Culture

• Flat Research Hierarchy: Minimal bureaucracy with direct collaboration alongside Strategy Partners and Portfolio Managers, ensuring rapid research-to-production cycles.
• Open Factor Ecosystem: Complete access to a globally shared factor library, operator infrastructure, and feature pipelines—no information silos or redundant effort.
• AI-Native Workflow: We actively leverage AI agents, LLMs, and intelligent development tools to augment research. We prioritize system architecture, mathematical rigor, and logic verification over manual boilerplate coding.

Key Responsibilities

• AI-Driven Alpha Discovery: Utilize AI workflows to rapidly translate top-tier academic literature into executable backtests (Paper-to-Code), mining high-capacity Alpha signals from Level-2/Tick, order book, and alternative datasets.
• Feature Engineering & Modeling: Train and evaluate advanced models (Transformers, GNNs, Time-Series Models, GBDT) with strict anti-overfitting protocols (cross-validation, signal denoising).
• Workflow Automation: Integrate LLMs and autonomous AI agents into daily research pipelines to automate hyperparameter tuning, factor generation, and real-time PnL attribution.
• Architecture & Code Auditing: Act as a quantitative code architect to review, optimize, and audit AI-generated code for execution efficiency, logical consistency, and look-ahead bias prevention.

Qualifications

• Education: Master’s or Ph.D. in Computer Science, Mathematics, Physics, Statistics, or Financial Engineering.
• AI-Native Competency:
• Expert command of AI development tools and prompt engineering to build agent workflows.
• Quantitative Foundation: Solid grounding in probability theory, linear algebra, time-series forecasting, and machine learning principles.
• Mindset: Highly self-driven, detail-oriented, and deeply committed to transparent, collaborative research.

Preferred Experience

• 0–3 years of Alpha research experience in quantitative funds or proprietary trading desks with a verifiable track record.
• Experience fine-tuning LLMs, building RAG architectures, or designing RL/AI Agents for financial applications.
• ACM/ICPC awards, Kaggle top placements, or publications in top AI conferences (NeurIPS, ICML, KDD).