About the role

We’re looking for ML Performance Engineers to join a scientific led systematic trading firm to design, optimize, and deploy large-scale machine learning systems that directly impact trading performance. You’ll optimize large-scale deep learning and LLM pipelines, turning cutting-edge research into measurable P&L impact. Day to Day: Build and optimize large-scale ML training & inference pipelines Enhance deep learning frameworks (PyTorch, JAX, Tensor Flow) for performance Debug GPU, memory, and distributed training bottlenecks Collaborate with researchers to deploy models in live trading systems
What We’re Looking For: Strong ML fundamentals (transformers, LLMs, attention, RLHF)Deep GPU expertise (CUDA, Tensor Cores, warp-level ops)Proficiency in Python & C++Knowledge of deep-learning frameworks like PyTorch, JAXGPU Libraries and tools – Triton, CUB, CuDNN, cuBLASWhy Join: Work with world-class researchers solving some of finance’s hardest problems with extensive room to push boundaries. Expect technical depth, real-world impact, and a culture that prizes curiosity, rigor, and speed. Apply or get in touch for more info!

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JOB OVERVIEW

Experience level

Senior

Location

New York, NY

Occupation

Financial Quantitative Analysts

Industry

Portfolio Management and Investment Advice

Posted

2 days ago

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Machine Learning Performance Engineer - Quant Research & Trading...