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JPMorgan Data Scientist Associate Sr - Artificial Intelligence Engineer NLP 
India, Karnataka, Bengaluru 
363152729

25.06.2024

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
  • 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

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 3+ years applied experience
  • 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
  • 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