Software Engineer II - AI/ML

JP Morgan Chase; Plano (TX); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Health Care Coverage

On-Site Health and Wellness Centers

Retirement Savings Plan

Backup Childcare

Tuition Reimbursement

Mental Health Support

Financial Coaching

Job summary

JP Morgan Chase in Plano, TX is seeking a software engineer to design, develop, test, and operate secure, scalable ML-enabled systems, including data pipelines, model deployment, monitoring, and performance management.

You will promote responsible AI usage, improve operational stability through automation, and contribute to architectural decisions across teams while collaborating with cloud-native tooling and ML teams.

Qualifications

• Requires formal training or certification in software engineering concepts.
• At least two years of applied software engineering experience.
• At least one year building or operating production ML-enabled systems.
• Strong programming and computer science fundamentals.
• Experience with cloud-native and ML tooling, SDLC and Agile practices.
• Ability to guide secure, responsible AI adoption and communicate technical concepts across teams.

Responsibilities

• Design, develop, test, and operate secure, scalable software and production ML systems including data pipelines, model deployment, monitoring and performance management.
• Promote responsible use of approved AI-assisted engineering tools and automate operational tasks to improve stability.
• Contribute to technical and architectural decisions across teams.

Skills

Python

Java

Distributed Systems

Machine Learning

MLOps

Data and Feature Pipelines

Model Training and Evaluation

Model Deployment and Monitoring

Spark

SQL

Airflow

Docker

Kubernetes

AWS

CI/CD

Responsible AI

Education

Tools

Docker

Kubernetes

Spark

Airflow

AWS

CI/CD

Job description

Design, develop, test, and operate secure, scalable software and production machine-learning systems, including data pipelines, model deployment, monitoring, and performance management. Promote responsible use of approved AI-assisted engineering tools, improve operational stability through automation, and contribute to technical and architectural decisions across teams.

Requirements: Requires formal training or certification in software engineering concepts, at least two years of applied software engineering experience, and at least one year building or operating production ML-enabled systems. Candidates should have strong programming and computer science fundamentals, experience with cloud-native and ML tooling, SDLC and agile practices, and the ability to guide secure, responsible AI adoption and communicate technical concepts across teams.

Key Skills: Python, Java, Distributed Systems, Machine Learning, MLOps, Data and Feature Pipelines, Model Training and Evaluation, Model Deployment and Monitoring, Spark, SQL, Airflow, Docker, Kubernetes, AWS, CI/CD, Responsible AI

Benefits: Health Care Coverage, On-Site Health and Wellness Centers, Retirement Savings Plan, Backup Childcare, Tuition Reimbursement, Mental Health Support, Financial Coaching