AI Pre-Training Engineer — Massive GPU Scale

OP Recruiting; Chicago (IL); On-site; USD 160,000 - 260,000; Full time

Job summary

OP Recruiting seeks an AI Research Engineer to advance large-scale pre-training capabilities, architecting and deploying foundation models over extensive GPU infrastructure. The role involves collaboration with ML researchers to design architectures and compute roadmaps, and translating DL methods into production-grade trading models.

Applicants should have deep DL systems experience and proficiency with PyTorch, CUDA, JAX, Triton, or XLA.

Qualifications

• 2+ years of hands-on professional experience engineering deep learning systems.
• Deep expertise in modern hardware acceleration and deep learning frameworks (PyTorch, JAX, CUDA, Triton).
• Proven track record of developing or tuning low-level training infrastructure or distributed training workflows.
• Ability to solve open-ended systems performance challenges without relying on off-the-shelf software.
• No prior finance background required.

Responsibilities

• Optimize distributed deep learning pre-training, focusing on networking, memory, data pipelines, and fault tolerance.
• Collaborate with ML researchers to co-design network architectures and compute roadmaps.
• Write high-performance lower-level code and custom kernels for large-scale GPU infra.
• Translate cutting-edge deep learning methods into production-grade trading models.

Skills

DL systems experience

High-performance computing

Tools

PyTorch

CUDA

JAX

Triton

XLA

Job description

OP Recruiting seeks an AI Research Engineer to advance large-scale pre-training capabilities, architecting and deploying foundation models over extensive GPU infrastructure. The role involves collaboration with ML researchers to design architectures and compute roadmaps, and translating DL methods into production-grade trading models.

Applicants should have deep DL systems experience and proficiency with PyTorch, CUDA, JAX, Triton, or XLA.