Software Engineer III - AI/ML

Job Description
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorgan Chase within the Risk Technology, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
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 on software engineering concepts 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.