The Research Engineering team is dedicated to accelerating the velocity of machine learningresearch and expanding the exploration space for innovations at PDT. We partner with PDT’s quantitative researchers to design and build astate-of-the-artenvironment for testing ideas rapidly and efficiently.
Research at PDT requires significant compute, and as such, we are looking for a talented engineerwith in-depth knowledge of ML techniques andDL ecosystemto help us build the infrastructure capable of supporting complex scientific research at scale.
Why join us? PDT Partners has a stellar 30+ year track record and a reputation for excellence. Our goal is to be the best quantitative investment manager in the world. PDT’s exceptional employee-retention rate speaks for itself. Our people are intellectually curious, collaborative, down-to-earth, and diverse.
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.
Incorporate advancements in machine learning, hardware acceleratorsand 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.
Below is a list of skills and experiences we think are relevant:
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.)
Experience with hardware accelerators.
Previous experience in Quant Finance is not required.
We encourage you to apply even if you don’t think you’re a perfect match.
The salary range for this role is between $190,000 and $250,000. This range is not inclusive of any potential bonus amounts. Factors that may impact the agreed upon salary within the range for a particular candidate include years of experience, level of education obtained, skill set, and other external factors.
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