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Sobre este puesto de Software Engineer - Distributed Compute en Hudson River Trading

Hudson River Trading · Presencial · Singapore

Hudson River Trading (HRT) is one of the top algorithmic trading companies in the world. Our research cluster is the backbone of our success; it’s where all of our trading strategies are generated.

We use a large, customized research environment with highly advanced CPU and GPU compute, storage, and networking technology. Our team thinks about the entire software stack, from the user-level API to optimizing performance out of low-level caching. We deal with everything from the theoretical, like fair resource scheduling, to the concrete, like optimizing a trader’s new program run-time performance. 

As a distributed compute engineer in a user-facing environment, you’ll develop and improve on technical solutions that make research as easy and efficient as possible. You’ll work every day with both talented quantitative traders and software engineers across all trading teams.

Responsibilities

  • Ensure HRT’s research environment is best in class, with a focus on user workloads
    • Maintain and improve resource scheduling, data caching, and job monitoring to make research as easy, fast, and efficient as possible, using both in-house and open source solutions
    • Optimize workloads at the user level to speed up user iteration speed
    • Tune workloads at the infrastructure level to make them more resource-efficient
    • Share metrics and real-time information with users to give insight into workload behavior
    • Sit down with users to understand their specific technical needs
  • Contribute individually and through leadership and coordination of the above
  • Set technical direction for the platform and take holistic ownership of the software infrastructure that supports Algo research

Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, or a related field
  • Strong C++ expertise (daily use preferred)
  • Python familiarity preferred
  • Experience collaborating closely with quantitative researchers and traders to understand their needs
  • Great communication capabilities
  • Superior design, debugging, and problem solving skills
  • Knowledge of UNIX operating systems (we use Linux), system/processor performance, and network communication

Culture

Hudson River Trading (HRT) brings a scientific approach to trading financial products. We have built one of the world's most sophisticated computing environments for research and development. Our researchers are at the forefront of innovation in the world of algorithmic trading.

At HRT we welcome a variety of expertise: mathematics and computer science, physics and engineering, media and tech. We’re a community of self-starters who are motivated by the excitement of being at the cutting edge of automation in every part of our organization—from trading, to business operations, to recruiting and beyond. We value openness and transparency, and celebrate great ideas from HRT veterans and new hires alike. At HRT we’re friends and colleagues – whether we are sharing a meal, playing the latest board game, or writing elegant code. We embrace a culture of togetherness that extends far beyond the walls of our office.

Feel like you belong at HRT? Our goal is to find the best people and bring them together to do great work in a place where everyone is valued. HRT is proud of our diverse staff; we have offices all over the globe and benefit from our varied and unique perspectives. HRT is an equal opportunity employer; so whoever you are we’d love to get to know you.

Please be advised: Use of AI tools by an applicant during interviews or assessments is strictly prohibited, unless otherwise instructed or agreed upon. We employ various methods to evaluate the authenticity of candidate responses. If we determine that AI assistance was used by an applicant during an interview or an assessment, we reserve the right to immediately end the interview or assessment, disqualify the applicant’s candidacy and/or rescind any job offers extended.

You can review our Global Applicant Privacy Notice, which explains how we process applicant information.

 

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