Job responsibilities
- Design, deploy and manage prompt-based models on LLMs for various NLP tasks in the financial services domain
- Conduct research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field
- Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization
- Communicate effectively with both technical and non-technical stakeholders
- Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs
- Develop and maintain tools and framework for prompt-based model training, evaluation and optimization
- Analyze and interpret data to evaluate model performance to identify areas of improvement
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Experience with prompt design and implementation or chatbot application
- Programming skills in Python with experience in PyTorch or TensorFlow
- Thorough knowledge of deep learning concepts, including attention mechanisms, transformers, and language modelling
- Experience in data pre-processing, feature engineering, and data analysis
- Excellent problem-solving and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner
- Ability to work in a fast-paced environment on multiple projects simultaneously
- Basic knowledge of deployment processes, including experience with GIT and version control systems for efficient collaboration and code management in MLOps projects
- Familiarity with data structures and algorithms, enabling effective problem-solving and optimization in machine learning workflows
- Hands on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environment
Preferred qualifications, capabilities, and skills
- PhD in Computer Science, Data Science or related field
- Experience in developing and deploying production-grade NLP models in the financial services industry
- Knowledge of financial products and services including trading, investment and risk management
- Familiarity with machine learning frameworks like scikit-learn and Keras
- Experience in developing APIs and integrating NLP models into software applications