Data Software Engineer III- ML
JobID: 210726404
Category: Software Engineering
JobSchedule: Full time
Posted Date: 2026-04-01T12:51:00+00:00
JobShift: Day
:
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Data Software Engineer III at JPMorganChase within the Commercial and Investment Bank, you will partner with Data Scientists to create cloud-based frameworks for hosting and operating models, applying SDLC and MLOps best practices to ensure reliability, security, and performance. You will leverage both internal and public cloud platforms with a mix of proprietary and open-source tools, collaborating closely with platform developers and engineering communities to integrate and evolve existing and new technologies
Job responsibilities
Develop and maintain secure, high-quality applications using Python and AWS
Produce architecture and design deliverables; contribute to solution design and reviews
Integrate AI/ML solutions into complex, domain-specific processing systems
Participate in code reviews, design discussions, and agile planning ceremonies
Collaborate with SRE and monitoring teams to ensure reliability, performance, and observability
Contribute to engineering communities of practice and technology events
Embrace continuous learning and creative problem-solving with a can-do mindset
Required qualifications, capabilities, and skills
Formal training in software engineering concepts and 3+ years of applied experience
Hands-on Python application development experience
Proven experience developing, debugging, and maintaining production applications
Solid understanding of software development best practices including version control, testing, and CI/CD
Strong problem-solving, communication, and collaboration skills, with the ability to convey design choices and communicate effectively with stakeholders
Familiarity with Machine Learning Operations (MLOps)
Experience using AI engineering tools (e.g., GitHub Copilot) for JIRA, documentation, coding, and releases, demonstrating measurable productivity and quality improvements.
Preferred qualifications, capabilities, and skills
AWS (hands-on): Glue, EventBridge, Step Functions, Lambda, ECS, EKS, Kinesis, CloudWatch
Outside AWS: Python, Terraform, TigerGraph, graph databases, GitHub Copilot, Airflow, Kubernetes
JPMC platforms/tools (highly preferred): Jules/JET, GKP (Gaia Kubernetes), Fusion MLOps