Quant ML Researcher for Systematic Investing

Referment; New York (NY); On-site; USD 130,000 - 190,000; Full time

Job summary

Referment is hiring a machine learning researcher to tackle complex quantitative research in systematic investing. You will own the full research lifecycle from hypothesis through to scalable deployment and real-world application.

You will combine deep machine learning expertise with strong empirical judgment to explore new architectures and training methods, testing generalisation and efficiency on large data sets.

Qualifications

• Deep expertise in machine learning and strong mathematical foundations.
• Excellent experimental judgment and ability to form testable hypotheses.
• Excellent programming skills with end-to-end research-to-production capability.

Responsibilities

• Develop and evaluate machine learning approaches for quantitative research problems.
• Form hypotheses and design rigorous experiments around predictive performance, robustness and generalisation.
• Explore new model architectures, representations, objectives and learning techniques.
• Prototype and benchmark ideas using large financial and other complex datasets.
• Improve training and implementation efficiency, including GPU optimisation where useful.
• Collaborate with researchers and developers to move successful ideas toward real-world application.

Skills

Deep ML knowledge

Experimental judgment

Python programming

GPU optimisation

Education

Bachelor's degree or higher in a relevant field

Tools

PyTorch

JAX

CUDA

XLA/Triton

Job description

Referment is hiring a machine learning researcher to tackle complex quantitative research in systematic investing. You will own the full research lifecycle from hypothesis through to scalable deployment and real-world application.

You will combine deep machine learning expertise with strong empirical judgment to explore new architectures and training methods, testing generalisation and efficiency on large data sets.