Machine Learning Engineer
SweedFull Time
Mid-level (3 to 4 years)
Key technologies and capabilities for this role
Common questions about this position
The role requires 3+ years of relevant experience as a Data Engineer or similar roles.
Candidates need proficiency with Python-based tools like Jupyter notebook and coding standards like PEP8, practical experience with deep neural networks and machine learning techniques, and the ability to implement data science pipelines and real-time applications in Python (C++ is a plus). Experience with LLM/AI for data processing is also a plus.
A strong academic background with a minimum of a bachelor’s degree in a technical or quantitative field is required.
WorldQuant has a culture that pairs academic sensibility with accountability for results, encouraging open thinking, challenging conventional ideas, and continuous improvement in a relaxed yet intellectually driven environment where excellent ideas come from anyone.
Strong candidates demonstrate intellectual horsepower, outstanding talent, exceptional analytical and problem-solving abilities with strong attention to detail, and the ability to collaborate with quantitative researchers and technologists.
Quantitative asset management using algorithms
WorldQuant is a quantitative asset management firm that focuses on managing investments for institutional clients like pension funds and sovereign wealth funds. The firm uses data and predictive algorithms to analyze financial markets and identify investment opportunities. Its approach involves algorithmic trading, where mathematical models guide investment decisions. Unlike many competitors, WorldQuant encourages a culture of experimentation and innovation among its employees, allowing everyone to contribute ideas regardless of their position. The company's goal is to generate returns for its clients while maintaining a commitment to equal opportunity in the workplace.