Applied Artificial Intelligence Machine Learning, Sr Associate

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Asset & Wealth Management

Senior Associate role focused on developing and implementing GenAI and Agentic AI solutions for financial services, involving data collection, model experimentation, deployment, and stakeholder communication. The role emphasizes applying LLMs and ML techniques to solve business problems and enhance client services.

What you'd actually do

  1. Develop and implement GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes.
  2. Collaborate with internal stakeholders to identify business needs and develop NLP/ML solutions that address client needs and drive transformation.
  3. Apply large language models (LLMs), machine learning (ML) techniques, and statistical analysis to enhance informed decision-making and improve workflow efficiency, which can be utilized across investment functions, client services, and operational process.
  4. Collect and curate datasets for model training and evaluation.
  5. Perform experiments using different model architectures and hyperparameters, determine appropriate objective functions and evaluation metrics, and run statistical analysis of results.

Skills

Required

  • Advanced degree (MS or PhD) in a quantitative or technical discipline or significant practical experience in industry
  • Minimum of 4 years of experience in applying NLP, LLM and ML techniques in solving high-impact business problems, such as semantic search, information extraction, question answering, summarization, personalization, classification or forecasting
  • Advanced python programming skills with experience writing production quality code
  • Good understanding of the foundational principles and practical implementations of ML algorithms such as clustering, decision trees, gradient descent etc.
  • Hands-on experience with deep learning toolkits such as PyTorch, Transformers, HuggingFace
  • Strong knowledge of language models, prompt engineering, model finetuning, and domain adaptation
  • Familiarity with latest development in deep learning frameworks
  • Ability to communicate complex concepts and results to both technical and business audiences

Nice to have

  • Prior experience of developing solutions for Financial domain
  • Exposure to distributed model training, and deployment
  • Familiarity with techniques for model explainability and self-validation

What the JD emphasized

  • Minimum of 4 years of experience in applying NLP, LLM and ML techniques in solving high-impact business problems
  • Advanced python programming skills with experience writing production quality code
  • Hands-on experience with deep learning toolkits such as PyTorch, Transformers, HuggingFace
  • Strong knowledge of language models, prompt engineering, model finetuning, and domain adaptation

Other signals

  • design autonomous AI agents
  • Develop and implement GenAI and Agentic AI solutions
  • Apply large language models (LLMs)
  • Collect and curate datasets for model training and evaluation
  • Perform experiments using different model architectures and hyperparameters
  • Monitor and improve model performance
  • Collaborate with technology teams to deploy and scale the developed models in production