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Vatic Investments

Quantitative trading with autonomous AI agents

Quantitative Developer

Applied Machine Learning +2Confirmed live in the last 24 hours
Full-timeNew York, NY, USA$150k - $350k /yrIn-person

About the Job

Requirements

  • Earned or will earn a Bachelor's degree in Computer Science, Electrical Engineering, Mathematics or related field
  • 2+ years’ experience building high-performance, distributed software
  • Deep understanding of C++ and Python in a Linux environment, with an emphasis on low latency and distributed computing
  • Strong understanding of machine learning, statistical learning, or deep learning methods and technologies
  • Performance tuning/optimization of software and algorithms
  • Exposure to high-performance computing
  • Innate curiosity for understanding why and how the markets work

Responsibilities

  • Collaborate with our team to build and rapidly scale state-of-the-art algorithmic trading systems
  • Work alongside computer scientists and researchers helping to enhance their productivity by developing innovative code that enables their work to be rapidly tested and applied to the markets
  • Quantitative Developers are integral in bringing ideas to life and creating real-time solutions

About the Company

Vatic Investments

Quantitative trading with autonomous AI agents

Vatic Investments operates as a quantitative trading firm where traders, AI researchers, and technologists collaborate to create autonomous trading agents and advanced technology for financial markets. Its products use proprietary algorithms and AI to analyze data, predict market moves, and automatically execute trades, aiming to improve market efficiency and transparency. The company differentiates itself by combining cross-disciplinary expertise and in-house, data-driven trading systems that operate autonomously, rather than relying on manual strategies alone. Its goal is to deliver superior trading solutions and insights while generating profits from data-driven trading activities.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
San Francisco, CA
Founded
2013

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