JPMorgan Data Scientist Lead - Artificial Intelligence Engineer 

India, Karnataka, Bengaluru 

831256755

Asset & Wealth Management: With client assets under supervision of $2.3 trillion and assets under management of $1.7 trillion, JPMorgan Asset & Wealth Management (AWM) is one of the largest asset and wealth managers in the world. Asset & Wealth Management offers global investment management in equities, fixed income, real estate, hedge funds, private equity, liquidity, and multi-asset solutions. It also provides trust and estate, banking and brokerage services to high-net-worth clients, and retirement services for corporations and individuals.

About the role:

AI Engineer – NLP: 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
• Excellent communication skills, with the ability to effectively communicate technical concepts to 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

Minimum Qualifications:

• Master’s degree or higher in Computer Science, Engineering or related field
• At least 6 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
• 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 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:

• 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