Software Engineer - Distributed Compute

Wehrtyou

Greater London

On-site

GBP 150,000 - 225,000

Full time

14 days+

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Benefits offered by this job

Discretionary performance-based bonus
Competitive benefits package

Job summary

Hudson River Trading (HRT) seeks a distributed compute engineer to advance our research environment. You will develop solutions that simplify and accelerate research workloads, collaborating daily with quantitative traders and software engineers across trading teams.

Ideal candidates bring strong C++ expertise, experience with UNIX/Linux systems, and the ability to design robust software infrastructure for high-performance research platforms.

Qualifications

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

Responsibilities

  • Maintain and improve resource scheduling, data caching, and job monitoring for a best-in-class research environment.
  • Optimize workloads at the user and infrastructure level to speed up iteration speed and improve efficiency.
  • Set technical direction for the platform and own the software infrastructure for Algo research.
  • Lead and coordinate efforts to deliver high-impact compute solutions for researchers and traders.

Skills

C++
Python
UNIX / Linux
Collaboration with researchers
Communication
Software design & debugging
Unix performance

Education

Bachelor's degree in CS/CE or related field

Job description

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 everyday 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

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

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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