Your Responsibilities:
Constructing scalable and resilient training and inference pipelines for deep learning.
Delving into the inner workings of open-source deep learning frameworks to enhance their capabilities.
Identifying and resolving performance bottlenecks.
Collaborating closely with researchers and fellow engineers.
Developing a comprehensive understanding of trading systems.
Requirements:
Proficiency in the inner workings of deep-learning frameworks such as PyTorch, JAX, TensorFlow, etc.
Thorough knowledge of computer architecture.
Proficiency in programming with C++ and Python.
Preferred Qualifications:
Experience with the JAX ecosystem, including XLA, Flax, etc.
Proficiency in programming for GPUs or other accelerators like CUDA, Triton, Pallas, etc.
Experience in Linux system programming.
Familiarity with large-scale distributed training.
Contributions to open-source projects in the realm of data science and machine learning.
