Description
As an AI Engineer, you will develop and optimize systems that integrate large language models (LLMs) , vector databases , and other AI technologies to enhance how our researchers analyze information, discover patterns, and generate ideas. You’ll work closely with quantitative researchers to translate complex market and research needs into intelligent, scalable solutions that support systematic trading innovation.
- Design and implement AI systems using LLMs, vector databases, and related tools for quantitative research applications such as literature review, data retrieval, and code generation.
- Deploy, monitor, and scale AI solutions in production, ensuring robust integration with existing infrastructure and real-time data pipelines.
- Collaborate with quant researchers and portfolio teams to build AI tools that accelerate discovery and improve decision-making.
- Stay at the forefront of AI and NLP research , contributing to internal innovation and thought leadership initiatives.
- Identify and mitigate risks related to AI use — including bias, data integrity, and model robustness.
- Continuously optimize performance and reliability of deployed AI models and systems.
Job Requirements
2+ years of hands-on experience developing or deploying LLMs, AI, or deep learning models in high-performance or production environments.Experience working with large-scale datasets and real-time data systems.Strong knowledge of modern NLP techniques and frameworks (e.g., tokenizers, transformers, embedding models).Proficiency with AI / ML tools and platforms, such as PyTorch, Hugging Face, or OpenAI APIs.Familiarity with financial data or algorithmic trading systems is a strong plus.Excellent analytical and problem-solving skills, with the ability to translate complex requirements into scalable technical solutions.