Machine Learning Performance Engineer - Quant Research & Trading

Acquire Me; United States; On-site; USD 200,000 - 350,000; Full time

Job summary

A leading systematic trading firm in the United States is seeking ML Performance Engineers to design and optimize large-scale machine learning systems. You will enhance deep learning frameworks and work closely with researchers in live trading systems. Ideal candidates have strong ML fundamentals and deep GPU expertise, with a competitive salary range between $200,000 and $350,000 annually.

Responsibilities

• Build and optimize large-scale ML training & inference pipelines.
• Enhance deep learning frameworks for performance.
• Debug GPU, memory, and distributed training bottlenecks.
• Collaborate with researchers to deploy models in live trading systems.

Skills

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, JAX

GPU Libraries and tools – Triton, CUB, CuDNN, cuBLAS

Job description

Overview

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.

Salary

Base pay range

$200,000.00/yr - $350,000.00/yr

This range is provided by Acquire Me. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Day to Day

• Build and optimize large-scale ML training & inference pipelines
• Enhance deep learning frameworks (PyTorch, JAX, TensorFlow) 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, JAX
• GPU Libraries and tools – Triton, CUB, CuDNN, cuBLAS

Why Join

Work with world-class researchers solving 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!

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Research, Information Technology, and Finance

Industries

• Technology, Information and Media, Research Services, and Financial Services