Machine Learning Performance Engineer

Selby Jennings; Chicago (IL); On-site; USD 140,000 - 210,000; Full time

Job summary

Selby Jennings in Chicago seeks a Performance Engineer to develop scalable ML infrastructure for training and inference at scale. You will focus on low-level optimization and high-performance data pipelines, enabling rapid experimentation and model deployment.

You should bring strong CUDA/C++ and Python skills, plus hands-on experience with PyTorch, TensorFlow, or JAX. Join a team at the intersection of finance and technology, driving innovation.

Qualifications

• BS or MS in CS or related field; strong fundamentals in algorithms and systems.
• Proven experience in GPU-accelerated ML workloads and optimization.
• Experience with deep learning frameworks and performance profiling.

Responsibilities

• Build scalable pipelines for deep learning training and inference.
• Optimize and extend ML frameworks for performance and functionality.
• Collaborate with researchers to accelerate experimentation and deployment.

Skills

CUDA

C++

Python

PyTorch

TensorFlow

JAX

Education

B.S. or M.S. in Computer Science

Job description

Join one of the top options market makers in the industry-a firm known for its innovation, cutting-edge technology, and commitment to transforming trading through AI and machine learning. They're building a high-performing ML team and seeking Performance Engineers to develop advanced infrastructure for training and inference at scale.

Unlike traditional trading firms that rely on star traders, market makers depend on elite technologists to build high-performance, data-intensive systems. If you're passionate about low-level optimization and want to work at the intersection of finance and technology, this is a unique opportunity.

What You'll Do

• Build scalable, robust pipelines for deep learning training and inference.


• Optimize and extend open-source deep learning frameworks for performance and functionality.


• Collaborate closely with researchers to accelerate experimentation and model deployment.

What You Bring

• Strong experience with low-level GPU programming using CUDA or similar.


• Deep understanding of deep learning frameworks such as PyTorch, JAX, or TensorFlow.


• Proficiency in C++ and Python, with a focus on performance engineering.


• B.S or M.S. in Computer Science or related field