ML Research Engineer for Scalable Trading AI

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

Benefits offered by this job

Global profit-sharing pool

Performance-based bonus

401(k) match up to 50%

Comprehensive health and life coverage

25 vacation days and holidays

Job summary

Optiver is seeking a Machine Learning Research Engineer to advance our AI initiatives in ML infrastructure, training, and inference for futures trading strategies. You will conduct innovative research on deep learning for price forecasting, build scalable training and inference pipelines, and contribute to open-source framework internals while collaborating with researchers and engineers.

Join a diverse team across 40+ countries, enjoy a competitive compensation package, and participate in a

Qualifications

• PhD or equivalent in ML/CS or related field.
• Experience building deep-learning models in PyTorch, JAX, or TensorFlow.
• Python programming experience.
• Research on large datasets and computationally intensive tasks.

Responsibilities

• Conducting innovative research on deep learning for price forecasting.
• Building scalable training and inference pipelines for deep learning.
• Diving into internals of open-source deep learning frameworks and enhance their functionality.
• Collaborating closely with researchers and other engineers.
• Developing an in-depth understanding of trading systems.

Skills

Python

Deep learning frameworks

Large datasets

C++ programming

Education

PhD or equivalent in ML/CS

Tools

CUDA

JAX ecosystem

Pallas

Open-source contributions

Job description

Optiver is seeking a Machine Learning Research Engineer to advance our AI initiatives in ML infrastructure, training, and inference for futures trading strategies. You will conduct innovative research on deep learning for price forecasting, build scalable training and inference pipelines, and contribute to open-source framework internals while collaborating with researchers and engineers.

Join a diverse team across 40+ countries, enjoy a competitive compensation package, and participate in a