A prominent high-frequency trading firm is actively seeking individuals with expertise in building and supporting large-scale deep learning models. In this role, you will be responsible for designing and implementing optimized machine learning solutions, spanning both infrastructure and application code. The firm encourages delving into the internals of open-source machine learning frameworks to enhance their capabilities. The position emphasizes close collaboration with traders, researchers, and fellow engineers, offering an opportunity to gain a profound understanding of trading theory and practice. If you are passionate about the intersection of finance and cutting-edge technology, this role provides a unique chance to contribute to a leading high-frequency trading firm's success.
Job Responsibilities:
* Develop and maintain large-scale deep learning models
* Create and deploy efficient machine learning solutions across infrastructure and application code
* Explore and enhance the functionality of open-source machine learning frameworks
* Foster collaboration with traders, researchers, and fellow engineers
* Acquire and deepen your understanding of trading theory and practice
Qualifications:
* Possess a minimum of 5 years of hands-on experience optimizing the performance of machine learning model training and inference
* Proficient in Python and a statically typed language, preferably C/C++
* Proven expertise in implementing distributed training techniques for machine learning models, utilizing deep learning frameworks such as TensorFlow, PyTorch, or JAX to accelerate model training and efficiently manage large datasets
* Skilled in GPU/TPU programming (CUDA, Triton, etc.)
* Demonstrated ability to lead and execute large-scale projects
* Strong collaboration skills with the capacity to work closely alongside developers and traders
