Worldquant6mo ago

Senior Python Engineer - AI Technology

Budapest · Budapestsenior

Data ScienceOtherPython Engineer1335 Backend Python Engineer

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Overview

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets.

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Data ScienceOtherPython Engineer1335 Backend Python Engineer

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform.

WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement.

Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.

Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers and portfolio managers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

Master's degree or higher in Computer Science, Engineering, or a related technical field from a top-tier institution.
5+ years of experience as a Python developer, with a strong focus on data engineering and AI/ML systems.
Expert-level knowledge of Python and its ecosystem, including experience with data processing libraries like Pandas, NumPy, and PySpark.
Proficiency in designing and implementing scalable, maintainable, and efficient data pipelines.
Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
Expertise in version control systems (Git), CI/CD practices, and agile methodologies.
Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
Experience in the finance industry is a plus but not required.
Experience with AI/ML frameworks such as PyTorch, or scikit-learn, LLM, agents or systems of agents is a significant plus.