PDT Partners

PDT Partners

Research Engineer

New York, NY · Senior

Sponsorship not specifiedDetected 107 days ago
Machine LearningTensorFlowPyTorchResearch

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odds of building a lasting career here

37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • The Research Engineering team is dedicated to accelerating the velocity of machine learning research and expanding the exploration space for innovations at PDT.
  • This is a hybrid position and will require the person to work from our New York City office at minimum 3 days a week.
  • Our goal is to be the best quantitative investment manager in the world.

Responsibilities

  • 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.
  • 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.
  • Exceptional programming skills and proficiency in identifying performance bottlenecks.
  • Experience with the p ython scientific stack and DL libraries ( PyTorch, Tensorflow, etc.)
  • Experience with hardware accelerators.

Benefits

  • Incorporate advancements in machine learning, hardware accelerators and high-performance computing to optimize research workflows.

Company info

  • Below is a list of skills and experiences we think are relevant. Even if you don't think you're a perfect match, we still encourage you to apply because we are committed to developing our people.
  • Even if you don't think you're a perfect match, we still encourage you to apply because we are committed to developing our people.

This listing is sourced directly from PDT Partners's careers page and normalized into a canonical job model.