Qualifications
Responsibilities:Perform original research in artificial intelligence, machine learning, and related quantitative disciplines. Create and test contemporary deep learning architectures. Process and analyze large, unstructured, and noisy datasets to derive significant insights. Collaborate with developers and fellow researchers to implement and refine trading strategies. Continuously investigate new methodologies and technologies to improve research outcomes. Requirements:A degree in mathematics, physics, computer science, or a related quantitative field (or expected within the next year). Understanding of machine learning, probability theory, and mathematical statistics. Proficiency in Python programming. Some familiarity with C++, although industrial experience is not required. Hands-on experience with modern deep learning architectures. Experience analyzing large, unstructured, and noisy datasets. Preferred: Published research in top-tier journals and conferences (ICML, NeurIPS, ICLR, CVPR, ICCV).
About the job
Join Pinely, an innovative algorithmic trading firm located in Amsterdam, where high-frequency trading meets cutting-edge research.
Our team excels in crafting resilient and adaptive trading strategies across diverse financial instruments and exchanges. We actively support the Olympiad movement, with many of our team members being distinguished mathematicians, researchers, and engineers.
As a Junior Deep Learning Researcher at Pinely, you will thrive in a dynamic HFT environment where your research will have an immediate impact. Our dedicated infrastructure team ensures seamless deployment and reliable experimentation at scale.
We foster a flat organizational structure that promotes autonomy, creativity, and a sense of ownership. Our informal, idea-driven culture celebrates innovation, valuing every contribution.
About Pinely
Pinely is a leading high-frequency trading firm in Amsterdam, dedicated to developing advanced algorithmic trading strategies. Our team comprises talented mathematicians and engineers who contribute to our innovative approach to financial markets.