Machine Learning Research Engineer

Posted 3 days ago

fintal partnersBrooklyn (NY)

Computer and Information Research Scientists All Other Professional, Scientific, and Technical Services

SENIORITY

Senior

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About the role

A leading proprietary trading firm is hiring a Machine Learning Research Engineer to join a major AI initiative applying advanced deep learning to financial markets. You'll work across model research, training and inference, developing approaches to price forecasting and building the infrastructure needed to turn research into practical trading applications. The team brings together deep learning expertise and trading knowledge, with particular interest in time series, transformers and scalable ML systems. Researchers and engineers from Big Tech, AI labs and other research-intensive environments are encouraged to apply. Prior trading experience is not required.

What you'll be doing:

Research and develop deep learning models for price forecasting, exploring approaches including transformers and time-series modelling
Build scalable, robust training and inference pipelines for large datasets
Explore and extend the internals of open-source deep learning frameworks to improve functionality and performance
Work closely with researchers, engineers and trading experts to translate research ideas into practical applications
Run experiments, evaluate results and iterate quickly in a fast-paced research environment
Develop an understanding of trading systems and the challenges of applying ML to financial markets

What we're looking for:

PhD or equivalent industry experience in machine learning or a related technical discipline
Strong experience building deep learning models using PyTorch, JAX or TensorFlowStrong Python programming skills
Research involving transformers, time series or other advanced deep learning architectures
Experience conducting computationally intensive research on very large datasets
A collaborative approach to solving complex technical problems
Additional experience valued
Experience with the JAX ecosystem, including XLA and FlaxGPU or accelerator programming using CUDA, Triton or PallasLarge-scale distributed training
Expertise in deep learning framework internals
Contributions to open-source ML projects or publications at conferences such as NeurIPS or ICMLC++ programming experience

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