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.
