JPMorgan Applied AI ML Analyst 

India, Karnataka, Bengaluru 

824190054

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:

• Bachelor’s degree or higher in Computer Science, Engineering or related field
• 3 years of experience in NLP and deep learning with recent exposure on prompt engineering on LLMs
• 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
• 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 environments
• Understanding of the software development lifecycle, with a focus on incorporating machine learning components and adhering to best practices in version control and code quality

Preferred Qualifications, capabilities and skills:

• Master’s or PhD in Computer Science, Data Science or related field
• Knowledge of financial products and services including trading, investment and risk management
• Familiarity with machine learning frameworks like scikit-learn and Keras
• Assess and choose suitable LLM tools and models for diverse tasks including but not limited to curating custom datasets and fine-tune LLM with a focus on parameter-efficient, mixture-of-expert, and instruction methods designing and developing advanced LLM prompts, Retrieval-Augmented Generation (RAG) solutions, and Intelligent agents for the LLMs and executing experiments to push the capability limits of LLM models and enhance their dependability.