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 Corporate Technology Consumer and Community Banking Risk Technology team 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
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Work with product managers, data scientists, ML engineers, and other stakeholders to understand requirements.
- Develop API/services for model deployment, ensuring scalability, reliability, and efficiency.
- Build applications to automate manual steps in MLOPs pipeline.
- Execute POC and for innovative ideas to solve complex business problems
- Stay informed about the latest trends and advancements in the latest LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.
- 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 of applied experience.
- Proficient in programming languages like Python for model development,
- Python for BigData i.e. Pyspark, Spark SQL on EMR experience
- web application/ APIs need experience with AWS lambda, cloud gateway etc.
- Experimentation, and integration with OpenAI API.
- Experience is building API and restful services using Flask/Django/FastAPI
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices design, implementation, and performance optimization.
- Understanding of fundamentals of machine learning and LLMs.
- Experience in applied AI/ML engineering, with a track record of deploying business critical machine learning models in production.
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies
- Familiarity with the financial services industries
