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JPMorgan Software Engineer III - AI/ML 
India, Karnataka, Bengaluru 
873775673

08.02.2025

Job responsibilities

  • Proactively develop an understanding of key business problems and processes.
  • Execute tasks throughout the model development process, including data wrangling/analysis, model training, testing, and selection.
  • Generate structured and meaningful insights from data analysis and modeling exercises, and present them in an appropriate format according to the audience.
  • Collaborate with other data scientists and machine learning engineers to deploy machine learning solutions.
  • Conduct ad-hoc and periodic analysis as required by business stakeholders, the model risk function, and other groups.
  • Adds to team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills

  • Formal training or certification onsoftware engineeringconcepts and 3+ years applied experience
  • Hands-on practical experience in ML projects, both supervised and unsupervised.
  • Proficient programming skills with Python, including libraries such as NumPy, pandas, and scikit-learn, as well as R.
  • Solid understanding and usage of the OpenAI API.
  • Experience with LLM & Prompt Engineering, including tools like LangChain, LangGraph, and Retrieval-Augmented Generation (RAG).
  • Experience with data and model serving using Flask, FastAPI, and Kubernetes.
  • Familiarity with other tools such as agent-based modeling frameworks (e.g., Reflection), Terraform, and Airflow.
  • Demonstrated experience working with large and complex datasets.
  • Experience in anomaly detection techniques and applications.
  • Excellent problem-solving, communication (verbal and written), and teamwork skills.
  • ⁠Experience with deep learning frameworks such as TensorFlow and PyTorch.

Preferred qualifications, capabilities, and skills

  • Experience with databases, including SQL (Oracle, Aurora), Chroma DB, and Vector DB
  • Familiarity with version control systems such as Bitbucket and GitHub.
  • Experience with graph analytics and neural networks.Experience with big data frameworks, with a preference for Spark, Hadoop, or Databricks.
  • Experience with CI/CD and DevOps practices, particularly using AWS or Azure pipelines.
  • Experience working with engineering teams to operationalize machine learning models.
  • Familiarity with the financial services industry.