ML Alpha Researcher

Machine Learning Alpha Researcher (NLP/LLM)

Overview

We are seeking a highly driven Machine Learning Alpha Researcher to develop and deploy cutting-edge NLP and LLM-based strategies for systematic trading. This role sits at the intersection of quantitative research, machine learning, and large-scale data engineering, with direct impact on alpha generation in fast-moving global markets.

Responsibilities

• Conduct research to identify and generate alpha signals using machine learning, with a strong focus on NLP and large language models
• Design, train, and evaluate models on large-scale structured and unstructured datasets (e.g., news, filings, transcripts, alternative data)
• Develop advanced text-processing pipelines, including entity recognition, sentiment analysis, topic modeling, and transformer-based architectures
• Apply state-of-the-art LLM techniques (fine-tuning, retrieval-augmented generation, embeddings, prompt engineering) to extract predictive insights
• Collaborate closely with traders, quantitative researchers, and engineers to translate research into production-ready models
• Optimize models for latency, scalability, and robustness in a live trading environment
• Continuously monitor and improve model performance using rigorous statistical validation and backtesting
• Stay at the forefront of machine learning and NLP research, evaluating new methodologies for alpha generation

Requirements

• Advanced degree (PhD) in Machine Learning, Computer Science, Mathematics, Physics, Statistics, or a related field
• Strong expertise in machine learning, deep learning, and NLP, including transformer architectures (e.g., BERT, GPT, etc.)
• Proven experience developing and deploying LLM-based solutions in research or production environments
• Exceptional programming skills in Python, with experience in ML frameworks (e.g., PyTorch, TensorFlow)
• Strong understanding of statistical modeling, time series analysis, and experimental design
• Experience working with large datasets and distributed computing systems
• Ability to translate complex research into practical, high-impact applications
• Strong problem-solving skills and intellectual curiosity

Preferred Qualifications

• Experience in quantitative finance, systematic trading, or alpha research
• Familiarity with market microstructure, financial data, or alternative datasets
• Knowledge of reinforcement learning or probabilistic modeling
• Experience with low-latency systems or real-time inference pipelines
• Publications in leading ML/NLP conferences or journals

What You'll Gain

• Opportunity to work on high-impact, real-world ML problems at scale
• Access to vast proprietary datasets and cutting-edge infrastructure
• Collaboration with world-class researchers, engineers, and traders
• A fast-paced, intellectually challenging environment focused on innovation and performance
• Competitive compensation and strong career growth potential

Ideal Candidate Profile

You are a deeply technical researcher who thrives on solving complex problems and pushing the boundaries of machine learning. You combine strong theoretical grounding with practical implementation skills and are excited about applying NLP/LLM techniques to extract signal from noisy, real-world data.