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Machine Learning Performance Engineer

Fintal Partners

A leading global trading firm is hiring a Machine Learning Performance Engineer to work on a flagship AI program. You'll have real influence across ML infrastructure, training and inference, work that feeds directly into the firm's futures trading strategies.

The role

  • Build robust, scalable training and inference pipelines for deep learning
  • Work inside the internals of open-source deep learning frameworks and extend what they can do
  • Hunt down and remove performance bottlenecks
  • Partner closely with researchers and fellow engineers
  • Build deep knowledge of how the trading systems work

What's on offer

  • You'll be part of a collaborative, high-performing culture built around curious thinkers and inventive problem-solvers, tackling some of the hardest challenges in financial markets alongside genuinely strong colleagues.
  • Colleagues drawn from 40+ nationalities
  • Highly competitive compensation
  • Firm-wide profit share plus performance-linked bonus
  • 401(k) matched up to 50%
  • Full health, mental health, dental, vision, disability and life cover
  • 25 days' paid leave plus market holidays
  • Generous office perks — breakfast, lunch and snacks, social events, clubs and sports leagues

What you'll bring

  • Strong low-level GPU programming in CUDA — Tensor Cores, cooperative groups, graphs, warp-level intrinsics
  • Deep familiarity with the internals of frameworks such as PyTorch, JAX or TensorFlow
  • Solid grounding in computer architecture
  • C++ and Python

Bonus points for

  • The JAX ecosystem (XLA, Flax and similar)
  • GPU tooling — Triton, CUB, cuDNN, cuBLAS
  • Linux systems programming
  • Large-scale distributed training
  • Open-source contributions in ML or data science

About the firm

A major market maker active on 100+ exchanges worldwide, focused on improving markets by adding liquidity, pricing accurately and increasing transparency in all conditions — with the health and efficiency of those markets a priority for every participant.

Vacancy posted 2 days ago
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