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Lead Quantitative Engineer/Architect

💼 Full-time🗓 2026-06-24

Core

Design, build, and maintain the core research and trading infrastructure for a systematic hedge fund, turning quantitative research ideas into production-ready systems.

Role type

Senior IC quantitative engineer/architect (systematic trading)

Builds

Production-ready research and trading systems, backtesting frameworks, data pipelines, and AI-enabled research tools

Domain

Quantitative finance / systematic trading

Deliverable

production ML models | product features | infrastructure

Required skills

Python, backend engineering, data structures and algorithms, software design, financial market data, time series analysis, backtesting frameworks, production system architecture, machine learning methods, feature engineering

Preferred skills

Hedge fund or prop trading firm experience, systematic trading strategies (equities, futures)

Technologies

Python, machine learning frameworks (regression, tree-based models, neural networks), data storage and ingestion tools

Responsibilities

Design and enhance systematic research and trading infrastructure; Implement and maintain backtesting frameworks and research pipelines; Productionize quantitative strategies and support live trading systems; Work with large financial datasets (market data, fundamentals, alternative data); Optimize performance, reliability, and scalability of research code; Build tools for data ingestion, cleaning, normalization, and storage; Collaborate with portfolio managers on model implementation and iteration; Assist with monitoring, debugging, and improving live strategies; Support the integration of machine learning techniques into quantitative research and signal development

Seniority

Senior, hands-on IC with technical lead responsibilities

Rewrite
## About the role We are a growing stealth-mode hedge fund focused on systematic and data-driven investment strategies. As we scale our research and trading capabilities, we are hiring a Quantitative Developer to help build and own the core research and trading infrastructure alongside the current team. This is a high-impact role with significant autonomy and direct influence on how strategies are researched, implemented, and deployed. ## Role Overview You will work closely with a lean team of our portfolio manager and quantitative researcher team to design, build, and maintain the systems that power our quantitative investment process. This role sits at the intersection of quantitative research, software engineering, and trading operations. You will help turn research ideas into robust, production-ready systems and shape the technical foundation of the firm. You will also contribute to the evaluation, implementation, and scaling of machine learning and AI-driven approaches that have contributed to alpha, spanning research workflows, data pipelines, and internal tools, in collaboration with other teams at the firm. ## Key Responsibilities Your work will directly impact fund performance and risk resilience. Your key responsibilities will be to: - Design and enhance our fully systematic research and trading infrastructure - Implement and maintain backtesting frameworks and research pipelines - Productionize quantitative strategies and support live trading systems - Work with large financial datasets (market data, fundamentals, alternative data) - Optimize performance, reliability, and scalability of research code - Build tools for data ingestion, cleaning, normalization, and storage - Collaborate closely with PMs on model implementation and iteration - Assist with monitoring, debugging, and improving live strategies - Support the integration of machine learning techniques into quantitative research, feature engineering, and signal development - Support the building and maintenance of AI-enabled research and productivity tools (e.g., model experimentation, data analysis, internal tooling) ## Required Qualifications - 7+ years of experience working in a backend role - 3+ years of experience working as a technical lead - 5+ years of experience working with Python - Solid understanding of data structures, algorithms, and software design - Experience working with financial market data and time series - Familiarity with quantitative research workflows and backtesting - Experience building or maintaining production systems - Ability to work independently and make sound technical decisions - Ability to work collaboratively with quantitative researchers and developers - Familiarity with machine learning methods (e.g., regression, tree-based models, neural networks) and their application to financial data ## Preferred / Nice to Have - 3+ years of experience in a hedge fund, prop trading firm, or quantitative asset manager - 3+ years of exposure to systematic trading strategies (equities, futures)
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