Quantitative Researcher (Deep Learning)

Stabile Search•Miami, FL

2d•Onsite

About The Position

This role is for a Quantitative Researcher with a machine learning background who is looking to apply their ML specialty on a sophisticated research platform. The quant research team is seeking talented researchers to bring machine learning techniques into their core research process, with no industry experience required. The position involves applying machine learning, including deep learning and large language models, directly to the research process. The output of the models is not theoretical but has a measurable, real-world P&L impact.

Requirements

No prior industry experience required
Strong quant researchers with an ML background
Proficiency in Python and ML frameworks such as PyTorch or TensorFlow
Deep knowledge of LLM architectures, including transformers and attention mechanisms
Understanding of GPU memory management, precision types, and parallelization techniques
Advanced training expertise across pre-training, fine-tuning, RLHF, and DPO
Familiarity with Retrieval Augmented Generation (RAG) systems
Strong mathematical and statistical foundations, particularly as they apply to quantitative finance
Comfort solving open-ended problems and designing end-to-end ML/AI solutions

Responsibilities

Conduct research and development in machine learning, with an emphasis on large language models and deep learning applications in quantitative finance
Design, implement, and optimize ML models for performance and scalability in a live financial context
Collaborate with cross-functional research and trading teams to integrate ML solutions into trading strategies and business processes
Work on models where the output isn't theoretical — it has a measurable, real-world P&L impact