Artificial Intelligence Researcher

AAA Global; West Palm Beach (FL); On-site; USD 130,000 - 230,000; Full time

Job summary

A leading global systematic investment firm seeks an AI Scientist to join its AI team. The role focuses on cutting-edge machine‑learning research and development of innovative models, signals, and AI‑driven tools used across the investment process.

The ideal candidate has a PhD in a quantitative field, at least two years of ML research experience, and strong programming skills in Python and C++, with PyTorch.

Qualifications

• PhD in a highly quantitative discipline is required.
• At least two years of ML research experience.
• Demonstrated creativity through original work or publications.
• Strong knowledge of ML, DL, and statistical methods required.
• Proficiency in Python and C++, with PyTorch experience.

Responsibilities

• Conduct machine-learning research to improve the systematic investment process.
• Develop predictive signals and AI-driven tools for trading.
• Apply LLMs and agentic AI to research and testing of trading signals.
• Design state-of-the-art deep-learning architectures.
• Collaborate with portfolio managers and engineers to improve models.

Skills

ML research

Deep learning

Python

C++

PyTorch

Statistical inference

Experiment design

Communication

Education

PhD in Computer Science/Mathematics/Statistics/ML

Tools

Git

CI/CD

Code review

Job description

A leading global systematic investment firm is seeking an exceptional AI Scientist to join its Artificial Intelligence team. The successful candidate will conduct cutting‑edge machine‑learning research and develop innovative models, predictive signals, and AI‑driven tools used throughout the investment process.

This position is suited to a highly creative researcher who combines strong academic foundations with practical problem‑solving skills and an interest in applying advanced AI techniques to financial markets.

Key Responsibilities

• Conduct machine‑learning research to improve multiple stages of the systematic investment process.
• Develop predictive and trading signals using innovative machine‑learning techniques.
• Apply large language models and agentic AI technologies to research, develop, and test new trading signals and investment algorithms.
• Design and implement state‑of‑the‑art deep‑learning architectures.
• Develop machine‑learning methods for signal compression, combination, and portfolio integration.
• Build scalable modeling frameworks and research tools for investment professionals.
• Run experiments, conduct statistical inference, and evaluate model robustness and performance.
• Collaborate closely with portfolio managers, quantitative researchers, and engineers to improve investment models and algorithms.
• Translate complex research findings into clear and practical recommendations.

Candidate Profile

• PhD in Computer Science, Mathematics, Statistics, Machine Learning, or another highly quantitative discipline.
• At least two years of professional or academic research experience applying machine learning to complex problems.
• Outstanding academic record and evidence of strong intellectual ability.
• Demonstrated creativity through original research, publications, inventions, or the development of novel methodologies.
• Advanced knowledge of machine learning, deep learning, statistical inference, mathematical optimization, or numerical solvers.
• Strong programming skills in Python and C++, with practical experience using PyTorch.
• Experience designing experiments, validating models, and interpreting statistical results.
• Familiarity with professional software‑development practices, including Git, continuous integration, automated testing, and code review.
• Excellent analytical judgment, attention to detail, and problem‑solving ability.
• Strong communication skills, with the ability to explain sophisticated technical concepts clearly.
• Prior financial‑market experience is advantageous but not essential.