ML Performance Engineer: Scalable DL Pipelines

Optiver; New York (NY); On-site; USD 180,000 - 220,000; Full time

Benefits offered by this job

Global profit-sharing pool

401(k) match up to 50%

Comprehensive health coverage

25 paid vacation days

Extensive office perks

Job summary

Optiver is seeking a Machine Learning Performance Engineer to join our team in New York. In this pivotal role, you will build scalable training and inference pipelines for deep learning and work closely with researchers to enhance performance in trading systems.

You will be part of a dynamic culture focused on collaboration and excellence, contributing to innovative AI initiatives that impact our futures trading strategies.

Qualifications

• Strong knowledge of low-level GPU programming with CUDA, including Tensor Cores and warp-level intrinsics.
• Expertise in internals of deep learning frameworks like PyTorch, JAX, TensorFlow.
• Deep understanding of computer architecture.
• Experience in C++ and Python.

Responsibilities

• Build scalable and robust training and inference pipelines for deep learning.
• Dive into internals of open-source deep learning frameworks and enhance their functionality.
• Identify and eliminate performance bottlenecks.
• Collaborate closely with researchers and other engineers.
• Develop an in-depth understanding of trading systems.

Skills

Low-level GPU programming with CUDA

Deep learning frameworks (PyTorch, JAX, TensorFlow)

Computer architecture

C++

Python

Tools

GPU libraries (cuDNN, cuBLAS)

Job description

Optiver is seeking a Machine Learning Performance Engineer to join our team in New York. In this pivotal role, you will build scalable training and inference pipelines for deep learning and work closely with researchers to enhance performance in trading systems.

You will be part of a dynamic culture focused on collaboration and excellence, contributing to innovative AI initiatives that impact our futures trading strategies.