ML Research Engineer - Quant Trading

Overview:

My client is a renowned quantitative trading firm specialising in deploying best-in-class programmatic models across global financial markets. Their tech team is lean, modern, and always seeking the best tools.

They seek an ambitious ML Engineer to join their flagship research team, which is transforming quantitative research and trading. This is an embedded role; the engineer sits directly with research teams, gaining insights into proprietary workflows. They will leverage the firm's cutting-edge platform to build scalable solutions that directly augment research capabilities and trading strategies, creating measurable impact.

Requirements:

• Strong coding experience in Python, C , or Rust, and expertise in writing production-grade, optimized code for ML training/inference.
• Demonstrable interest in HPC and ML Infrastructure, staying current with GPU/TPU architecture, parallel processing (CUDA/RoCM), and low-latency networking (InfiniBand/NVLink).
• Familiarity with distributed training frameworks (e.g., PyTorch Distributed, Horovod) and parallelism techniques (e.g., sharding, DeepSpeed).
• Experience with hardware resource management and monitoring (e.g., Slurm, KubeFlow, Prometheus) for managing large GPU/CPU clusters.
• Exceptional communication skills for technical and non-technical collaboration, especially for ML infra/hardware translation.
• Beneficial: Familiarity with ML model serving infra (e.g., Triton), low-level performance profiling (e.g., NVProf/NSight), or custom kernel optimization.

On Offer:

• Direct Impact: Clear visibility on how your optimization of GPU utilization and training throughput accelerates research and deployment for high-value ML teams.
• Cutting-Edge Technology: Work at the forefront of ML infrastructure, contributing to core libraries for optimized data loading and resource scheduling, shaping the scalable AI platform
• Tech-Led Culture: An environment prioritizing deep exploration and technical excellence in systems/performance engineering, with resources to solve hard distributed ML and infra problems.

Apply or get in touch for more details.