Senior Software Engineer - Research Platform

Quberesearchandtechnologies

Paris

Sur place

EUR 70 000 - 90 000

Plein temps

14 jours+

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Résumé du poste

Quberesearchandtechnologies in Paris is looking for an experienced professional to design and operate distributed services. You will develop platform APIs that enhance the productivity of quantitative researchers while improving the reliability and scalability of compute-intensive workflows.

The ideal candidate has 5+ years of experience in building large-scale distributed systems and is proficient in languages like C++, Java, or Rust. The company offers a dynamic work environment focused on innovation and work-life balance.

Qualifications

  • 5+ years of experience building and operating large-scale distributed systems.
  • Strong proficiency in systems programming languages.
  • Deep understanding of distributed systems and performance optimization.

Responsabilités

  • Design and operate services managing compute workloads.
  • Develop platform APIs improving productivity for researchers.
  • Enhance reliability, scalability, and performance of workflows.

Connaissances

C++
Java
Rust
Go
Distributed Systems
Performance Optimization

Formation

Bachelor’s, Master’s, or PhD in Computer Science or related field

Outils

HPC environments
PyTorch
TensorFlow

Description du poste

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology- and data-driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high-quality returns for our investors.

This role sits at the intersection of distributed systems, platform engineering, and high-performance computing. You will build and operate the foundational services that quantitative researchers rely on every day, including workload orchestration, scheduling, security, observability, and platform tooling.

Your Future Role Within QRT:
  • Design, build, and operate distributed services that manage compute workloads and data access across large-scale infrastructure
  • Develop platform APIs and tooling that improve the productivity of quantitative researchers
  • Improve the reliability, scalability, and performance of compute-intensive research workflows
  • Build solutions for scheduling, resource management, observability, and security
  • Partner closely with researchers and infrastructure teams to translate complex requirements into scalable platform capabilities
  • Take ownership of systems end-to-end, from design and implementation through production operation
Your Present Skill Set:
  • Bachelor’s, Master’s, or PhD degree in Computer Science or a related field, or equivalent practical experience
  • 5+ years of experience building and operating large-scale distributed systems in production environments
  • Strong proficiency in C++, Java, Rust, Go, or other systems programming languages
  • Deep understanding of distributed systems, concurrency, performance optimization, reliability, and fault tolerance
  • Experience designing and operating services, platforms, or infrastructure used by other engineers
Nice to have:
  • Experience with internal developer platforms, cloud infrastructure, orchestration systems, or HPC environments
  • Familiarity with GPU-accelerated workloads and modern ML frameworks such as PyTorch or TensorFlow
  • Experience supporting researchers, data scientists, or other highly technical users
  • Exposure to quantitative finance or large-scale data-intensive environments

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

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