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The Research Engineering team is dedicated to accelerating the velocity of machine learning research and expanding the exploration space for innovations at PDT. We partner with PDT’s quantitative researchers to design and build a state-of-the-art environment for testing ideas rapidly and efficiently. Research at PDT requires significant compute, and as such, we are looking for a talented engineer with in-depth knowledge of ML techniques and DL ecosystem to help us build the infrastructure capable of supporting complex scientific research at scale.
Job Responsibility:
Partner with the research team to understand future research directions and build the next generation of highly scalable infrastructure for alpha, signal, and portfolio construction
Incorporate advancements in machine learning, hardware accelerators and high-performance computing to optimize research workflows
Maintain, develop, and re-imagine the extensive internal research stack that continues to be a differentiating factor for PDT business
Optimize models for inference and use in real time trading systems
Requirements:
Experience with building infrastructure for training/fine-tuning large ML models
Intellectual curiosity and a strong interest in solving difficult problems
Exceptional programming skills and proficiency in identifying performance bottlenecks
Experience with the python scientific stack and DL libraries (PyTorch, Tensorflow, etc.)