Manhattan, United States
Machine Learning Performance Engineer - Trading
Manhattan, United States, New York, New York, us, 10261
Machine Learning Performance Engineer - Trading
Selby Jennings, Manhattan, United StatesPosted:
2 days agoJob Type:
In-Office JobEmployment Type:
PermanentSalary:
USD175000 - USD250000 per annumYour 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.
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Selby Jennings, Manhattan, United StatesPosted:
2 days agoJob Type:
In-Office JobEmployment Type:
PermanentSalary:
USD175000 - USD250000 per annumYour 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.
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