IT & Software

Senior Software Engineer - Research Technology

DRW

London · Greater London · United Kingdom

Overview

In this role you design and operate a high-performance data and simulation platform used by quant researchers and trading teams. You build scalable data pipelines, optimize throughput, and develop research tooling that accelerates backtesting and iteration. You will own simulation frameworks tightly integrated with live trading and help deploy quantitative models. You work hands-on, mentoring with a focus on reliability and efficiency to support fast, data-driven decision making.

Responsibilities
  • Design, build, and maintain high-performance, scalable software and data systems for quant researchers and trading teams
  • Implement raw exchange data pipelines in modern C++ for high-throughput ingestion
  • Orchestrate and improve reliability of data and compute pipelines on HPC clusters
  • Create ad-hoc computation frameworks and research tooling (Python + C++ integrations) for rapid slicing and backtesting
  • Develop and maintain simulation frameworks integrated with HFT/live trading platforms
  • Support training and deployment of quantitative models used in trading
  • Optimize codebases for performance, reliability, and resource efficiency across the stack
  • Hands-on contributor while mentoring junior team members as needed
Key requirements
  • 7+ years of experience building large-scale, high-performance systems; daily use of modern C++ (>=17) and Python
  • Strong CS fundamentals: data structures, algorithms, networking, OS, concurrency, system design
  • Experience running compute at cluster scale: job scheduling, resource management, retries, reliability
  • Slurm, Kubernetes, Ray, Spark, or internal schedulers
  • Proven data-engineering experience: schema design, storage formats, compression, I/O trade-offs, pipelines handling hundreds of terabytes
  • Experience with columnar formats such as Parquet or Arrow
  • Experience designing and operating services/platforms for data-intensive environments
  • Proven ability to ship production software safely and repeatedly with data-driven quality
  • problem-solving
  • collaboration
  • communication
  • Rust (desirable)
  • Slurm or other cluster schedulers
  • ML/Deep Learning frameworks (desirable)

Reference: WJ-747_30179262

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