JAX Engineer (Futures Trading) - Austin, TX

[Recruiter-Jim]

About the Role:​

We are seeking a highly motivated and skilled Applied Modern Deep Learning Framework (JAX) Engineer with CUDA expertise to join a growing team in Austin, TX. This role is critical to the development and implementation of advanced, GPU-accelerated deep learning models for filtering, analyzing, and predicting market behavior. You will be an integral part of a collaborative team, working closely with our quantitative researchers and algo engineers to translate complex financial data and trading strategies into practical, high-performance solutions. This is a fantastic opportunity to contribute to a high-impact project at the intersection of finance and cutting-edge AI, all while living and working in the vibrant city of Austin.

Responsibilities:

• Design, develop, and implement GPU-accelerated deep learning models using JAX and CUDA for filtering and predicting time series data relevant to futures markets (e.g., price movements, volatility, order book dynamics, related asset correlations).
• Optimize JAX and CUDA code for extreme performance and ultra-low-latency, essential for real-time futures trading, leveraging the GPU cluster.
• Collaborate closely with quantitative researchers to translate complex trading strategies and financial models into robust and efficient, GPU-accelerated code.
• Develop and maintain software libraries and tools to facilitate time series analysis and seamless model deployment within a high-performance, GPU infrastructure.
• Conduct rigorous backtesting and performance evaluation of models, ensuring accuracy, robustness, and profitability in live futures market conditions.
• Contribute to the development of data pipelines for efficient ingestion and preprocessing of high-frequency financial data, including data feeds.
• Stay up-to-date with the latest advancements in deep learning, JAX, CUDA, and model engineering, proactively identifying opportunities.
• Actively participate in team discussions and knowledge sharing, contributing to a collaborative environment.
• Communicate effectively with team members and stakeholders, presenting technical findings clearly and concisely.
• Contribute to code reviews and maintain high code quality standards.

Qualifications:

• Essential:
  • Extensive experience with JAX and its ecosystem (e.g., Flax, Haiku Internals).
  • Strong programming skills in Python/C++.
  • Proven expertise in CUDA programming and GPU optimization.
  • Solid understanding of deep learning principles and architectures, particularly for time series analysis (e.g., RNNs, LSTMs, Transformers, attention mechanisms, deep reinforcement learning).
  • Experience with training and optimizing deep learning models on large, noisy, and potentially non-stationary datasets, leveraging GPUs.
  • Familiarity with version control systems (e.g., Git).
  • Excellent problem-solving and analytical skills, with a strong quantitative aptitude.
  • Excellent communication and interpersonal skills, with a demonstrated ability to thrive in a collaborative team environment.
• Comp Range $500k+

James@njf.com