OUR COMPANY

Our Company

KNOW ABOUT US

Infinite Tech Global was co-founded by two visionaries, Mr. Thomas Payne (CEO) and Ms. Amelia Olson (CTO) who share a common vision of effectively harnessing the power of technology to realize stable, consistent profits in trading.

Infinite Tech Global was incepted as a partnership between our two co-founders, Ms. Amelia Olson and Mr. Thomas Payne to commercialize research discoveries in the field of Algorithmic/Quant Trading that were made during Mr Payne’s research work at the University of Geneva Research Computing Center.

Prior to establishing the HQ in Zurich, Switzerland, our co-founders, supported by our world-class team of technical and financial specialists accumulated a wealth of experience and carried out extensive R&D (Research & Development) in the trading, blockchain, software and AI analytics sectors.

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MISSION & VISION

Mission:

To develop cutting-edge arbitrage trading tools that effectively integrate technology into trading, thereby providing our clients with stable, consistent investment returns at minimal risk.

Vision:

To be a leader in the field of arbitrage trading and a world-class partner to our clients.

Meet Our Team

PROFESSIONAL TEAM

Thomas Payne

(CEO)

  • Co-founder of Infinite Tech Global
  • Key figure behind the development of the IQ Engine with his team of engineers in Zurich, Switzerland
  • Highly experienced in the fields of Programming, Enterprise Software, Artificial Intelligence and IoT systems
  • Senior software engineer at Swiss Joint Research Center in Switzerland
  • Senior Back-end Developer at Advanced Intelligent Systems
  • BSc in Computer Science (California Institute of Technology)
  • MSc in Computer Science (Cornell University)
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Amelia Olson

(CTO)

  • Co-Founder of Infinite Tech Global
  • Professor at California Institute of Technology, Computing and Mathematical Sciences
  • Ph.D. in Computer Science (Cornell University)
  • Carried out extensive research work in the fields of Cloud Computing and trading software algorithms