Faculty Fellow
Core
Conduct applied machine learning research using large-scale, real-world financial datasets to develop novel modeling techniques and translate theoretical insights into production-scale systems.
Role type
Faculty Fellow (Applied ML Researcher)
Builds
Production-scale ML systems and strategies for quantitative trading
Domain
Quantitative Finance / Machine Learning
Deliverable
production ML models
Required skills
Machine learning, Deep learning, Statistics, Python, PyTorch, TensorFlow, Jax, Theoretical foundation in ML
Preferred skills
Tenured or tenure-track faculty status, Newly minted PhD or Postdoc status, Experience in LLMs, Applied mathematics, Physics
Technologies
Python, PyTorch, TensorFlow, Jax
Responsibilities
Conduct applied ML research, Develop novel modeling techniques, Collaborate with researchers and engineers, Contribute to ML infrastructure design, Evaluate ideas in an industrial setting, Foster collaboration within the ML and academic ecosystems
Seniority
Senior, Research Fellow