AI Engineer: ML Deployments, Data Pipelines & Automation

CEI; Chester (Delaware County); Hybrid; USD 130,000 - 150,000; Full time

Job summary

CEI is seeking an AI Engineer to design, build, and deploy ML solutions for an AI-driven operations platform in West Chester, PA. The role focuses on automating tasks, reliability, and integrations, with a hybrid work setup.

You will work across data pipelines, model deployment, and platform architecture, collaborating with engineering, operations, and product teams to deliver impactful AI-powered automation.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Mathematics, or a related field.
• 3-5 years of experience in Machine Learning Engineering, Data Engineering, or Software Engineering.
• Strong programming experience with Python.
• Experience developing, deploying, and monitoring machine learning models in production.
• Hands-on experience with machine learning, deep learning, statistical analysis, or data mining.
• Experience building scalable data pipelines and processing frameworks.
• Knowledge of Kafka, Spark, Docker, and modern cloud technologies.

Responsibilities

• Design, train, validate, deploy, and monitor machine learning models.
• Build and maintain data pipelines for ingestion, validation, cleansing, and monitoring.
• Develop proof-of-concept solutions and evaluate emerging AI/ML technologies.
• Contribute to platform architecture, automation capabilities, and system integrations.
• Collaborate with engineering, operations, and product teams to deliver solutions.
• Create technical documentation, test plans, recommendations, and reports.
• Support testing, analysis, and continuous improvement initiatives.

Skills

Python

Machine learning

Data engineering

Software engineering

Education

Bachelor's degree in CS/CE/Math

Tools

Kafka

Spark

Docker

Cloud technologies

Job description

CEI is seeking an AI Engineer to design, build, and deploy ML solutions for an AI-driven operations platform in West Chester, PA. The role focuses on automating tasks, reliability, and integrations, with a hybrid work setup.

You will work across data pipelines, model deployment, and platform architecture, collaborating with engineering, operations, and product teams to deliver impactful AI-powered automation.