Senior AI/ML Software Engineer

JPMorganChase

Plano (TX)

On-site

USD 120,000 - 170,000

Full time

3 days ago

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Job summary

JPMorganChase in Plano, TX seeks a Software Engineer III to design, build, and optimize secure software components within a scalable, production-grade environment. You will work on AI-assisted engineering practices, collaborate across teams, and help drive reliable, resilient systems supporting consumer banking tools.

Ideal candidates bring 3+ years of software experience, strong Python, ML framework knowledge, and cloud ML platform exposure.

Qualifications

Formal training or certification on software engineering concepts and 3+ years applied experience.
Hands-on practical experience delivering system design, application development, testing, and operational stability.
Hands-on experience building, deploying, and maintaining machine learning platforms or infrastructure.
Proficiency in Python and one or more ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with data processing frameworks and tools (e.g., Spark, Pandas, SQL).
Practical experience with cloud-based ML platforms (e.g., AWS SageMaker, GCP AI Platform, Azure ML) or on-prem ML infrastructure.
Demonstrated experience leading effective use of approved AI-assisted software development tools with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations
Proficient in all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
In-depth knowledge of the financial services industry and their IT systems Practical cloud native experience

Responsibilities

Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems.
Develops secure and high-quality production code, and reviews and debugs code written by others.
Drives team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
Applies knowledge of SDLC tools and enterprise AI-assisted development to improve automation.
Identifies opportunities to automate remediation of recurring issues to improve stability.
Leaves evaluation sessions with external vendors and internal teams to assess architectures and applicability.
Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems.
Applies AI-assisted development tools to improve automation value.
Applies technical troubleshooting to break down solutions and solve problems of basic complexity.
Gathers, analyzes, and draws conclusions from large data sets to support secure, stable development.
Learns and applies system processes for secure, stable code and systems.