CAREERS

Machine Learning Engineer

Hanoi or Ho Chi Minh City, Vietnam

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.

The Role: WorldQuant is seeking an exceptional individual to join the firm as a Machine Learning Engineer. While prior finance experience is not required, a successful candidate must possess a strong interest in learning about finance and global markets. Machine Learning Engineers will design, code and implement complex proprietary pipelines, models and tools to drive our forecast business. You will collaborate with researchers and PM’s to gather, analyze and spec out requirements, develop/test code, and manage product deliverables. A successful candidate will help build the software that will be used by Portfolio Managers to construct portfolios.

What You’ll Bring:

  • M.Sc./Ph.D. from a leading university in a Computer Science, Engineering, or related discipline
  • Experience designing and operating complex machine learning models and data pipelines
  • Experience building distributed or data intensive systems
  • Excellent problem solving abilities, insight, and judgment as well as a strong attention to detail
  • Experience programming production systems in Python or C++
  • Experience working in Linux environments
  • Strong communication skills; ability to express complex concepts in simple terms
  • Understanding of basic probability, statistical inference, software solvers, mathematical optimization is a big plus
  • Experience building CI/CD pipelines is a big plus

What We Offer:

  • Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday
  • We offer a strong culture of learning and development: training courses, library, speakers, share and learn events
  • Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people
  • Employee resources groups with strong diversity and inclusion culture
  • Premium Health Insurance and Employee Assistance Program
  • Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family
  • Team building activities every month: Local engagement events, monthly team lunch – Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
  • Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams
  • Happy-hour with tea break, snacks and meals every day in the office!
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WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.