Worldquant28d ago

LLM Data Engineer

Hanoi Or Ho Chi Minh Citymid

EngineeringData ScienceData EngineeringData EngineerData & AI

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Quick Summary

Key Responsibilities

Degree in a quantitative or technical discipline (computer science, engineering, etc.

Technical Tools

EngineeringData ScienceData EngineeringData EngineerData & AI

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. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

The Role: As a LLM Data Engineer at WorldQuant, you will be at the heart of transforming unstructured text into actionable, high‑value insights that power quantitative investment strategies. This is a hands-on, engineering role where you’ll design, build, and scale the data pipelines that underpin our data research. This role is ideal for someone who loves building production systems, enjoys working deeply with text and large language models, and wants their engineering work to empower quantitative research at the firm. You’ll join a highly technical, collaborative environment where you work closely with Research and where your ideas can quickly translate into impact at scale.

What You’ll Bring:

Degree in a quantitative or technical discipline (computer science, engineering, etc.)
Basic knowledge of probability and statistical theory
At least 2 years’ experience in developing and managing scalable and robust data pipelines
Have a deep understanding of machine learning, and experience in training, inference, and evaluation.
Experience with LLM technologies and agentic systems
Excellent Python coding skills; familiarity with pandas / polars / duckdb is required
Strong analytical skills and attention to detail
Excellent communication skills in both verbal and written form
Ability to operate in a collaborative, team-oriented culture
Proactive and mature approach to problem-solving and project management
Experience with Kubernetes (k8s) for deployment is preferred
Experience with monitoring and alerting tools is preferred
Familiarity with infrastructure management and deployment and ML Ops is preferred