Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

Your future role within QRT

• Design, develop, and deploy state-of-the-art Generative AI models and agentic frameworks, delivering impactful solutions tailored to real-world challenges. 
• Collaborate with stakeholders to deeply understand problem statements and craft scalable, production-ready solutions within given constraints, balancing both development and architecture. 
• Utilize Advanced RAG techniques, incorporating late chunking, RHLF (Reinforcement Learning from Human Feedback), BFS (Breadth-First Search) and DFS (Depth-First Search) methods to optimize information retrieval and enhance generative model outputs  
• Optimize and fine-tune Large Language Models (LLMs) like GPT, BERT, etc., for use cases in natural language understanding, data processing, and predictive modelling. 
• Collaborate with cross-functional teams, including quants, researchers, and engineers, to harness AI/ML capabilities that drive our competitive edge in financial markets. 
• Stay ahead of the curve by experimenting with the latest AI/LLM technologies to continuously improve models and unlock new possibilities. 
• Oversee the processing of large, complex datasets for model training, ensuring data efficiency and integrity. 

Your present skillset

• Advance proficiency in Python, with extensive experience in building, training, and deploying AI/ML models. 
• Expertise in Generative AI and Large Language Models (LLMs), 
• Experience with AI frameworks and Agentic Frameworks such as AutoGen, OpenAI Agents, Bedrock, TensorFlow, PyTorch, or Hugging Face. 
• Strong understanding of Natural Language Processing (NLP) techniques, and how to apply them effectively using LLMs. 
• Deep knowledge of machine learning infrastructure, including model deployment, scaling, and real-time monitoring. 
• Strong problem-solving skills, with the ability to optimize models for specific tasks and drive performance improvements. 
• Excellent communication skills for effective collaboration with cross-functional teams.

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.