Machine Learning Engineer Llm For Quantitative Finance (Remote)

We are a cutting-edge, fully remote team disrupting the world of algorithmic trading by leveraging large language models (LLMs).

Our mission is to develop fully autonomous trading agents and make advanced AI more accessible.

We foster an open and collaborative environment, valuing diversity, continuous learning, and intellectual curiosity.

Role Summary

As a Senior Quantitative Researcher, you will be responsible for researching, developing, and implementing state-of-the-art algorithms to optimize the performance of LLMs for algorithmic trading. This includes:

Designing and developing innovative methods to enhance LLM architectures for financial market prediction and decision-making.
Building scalable and efficient pipelines for training and deploying LLMs.
Collaborating with software developers and data scientists to improve trading infrastructure.
Analyzing historical and real-time market data to identify trading opportunities and enhance strategy performance.
Optimizing and monitoring live trading algorithms to ensure consistent profitability.
Staying ahead of market trends, industry regulations, and emerging technologies.
Publishing research papers and presenting findings at top-tier conferences.
Ideal Candidate Profile

Education:

PhD or Master’s Degree in Computer Science, Statistics, Mathematics, Electrical Engineering, Physics, or related fields.
Technical Expertise:

Proven expertise in natural language processing (NLP) and generative AI.
Strong background in deep learning, particularly in LLM architectures.
Experience with large-scale LLM training frameworks such as PyTorch or TensorFlow.
Proficiency with GPU acceleration (CUDA) and distributed computing.
Solid programming skills in Python or C++ and familiarity with frameworks like Hugging Face or similar.
Strong mathematical understanding of AI principles and their integration into LLMs.
Experience with algorithmic trading platforms and statistical modeling.
Strong knowledge of market microstructure and financial instruments.
Proven success in developing and executing trading strategies.
Understanding of risk management practices in trading.
Skills and Mindset:

Strong analytical and problem-solving capabilities.
Self-driven, innovative, and collaborative.
Ability to work independently in a remote, cross-cultural environment.
Ability to thrive in a fast-paced, results-driven environment.
Demonstrated ability to generate impactful research in academic and professional pursuits.
What We Offer

The opportunity to work on groundbreaking LLM technologies in the exciting field of algorithmic trading.
Fully remote work environment with flexible hours.
Competitive salary and equity package.
Regular virtual team-building events and knowledge-sharing sessions.
Support for continued learning, conference attendance, and professional development.
A chance to make a significant impact in a rapidly growing field.
To Apply

Interested candidates should submit their resume, project portfolio, and publication list.