AI/ML Engineer — Production AI Systems & Deployment

CEI; Pittsburgh, Northern (Allegheny County, KY); Hybrid; USD 120,000 - 150,000; Full time

Job summary

Computer Enterprises, Inc. in Pittsburgh, PA is seeking an AI/ML Engineer to design, develop, and deploy production machine learning and artificial intelligence systems.

The roving role requires relocation to unanticipated locations across the United States and is on-site, with no travel schedule fixed at this time. The role involves model integration, validation, deployment, and translating business requirements into technical implementations using data-driven and software-based approaches.

Qualifications

• Bachelor's degree in Computer Science, Computer and Information Technology, Computer Science or a related field required.
• Two years of experience required. Relocation required.
• Some experience with Python, Databricks and MongoDB, Qwen, DeepSeek-R1, Phi-4, LLaMA, ChatGPT Vision API, AWS S3, Firebase, ReactJS, Apple Healthkit and IoT Sensor Data.

Responsibilities

• Design, develop, and deploy production ML/AI systems by implementing data-driven and software-based solutions.
• Model integration, validation, deployment, and translating business requirements into technical implementations.

Skills

Python

Databricks

MongoDB

Qwen

DeepSeek-R1

Phi-4

LLaMA

ChatGPT Vision API

AWS S3

Firebase

ReactJS

Apple Healthkit

IoT Sensor Data

Education

Bachelor's degree in Computer Science / Computer and Information Technology or related field

Tools

Python

Databricks

MongoDB

Qwen

DeepSeek-R1

Phi-4

LLaMA

ChatGPT Vision API

AWS S3

Firebase

ReactJS

Apple Healthkit

IoT Sensor Data

Job description

Computer Enterprises, Inc. in Pittsburgh, PA is seeking an AI/ML Engineer to design, develop, and deploy production machine learning and artificial intelligence systems.

The roving role requires relocation to unanticipated locations across the United States and is on-site, with no travel schedule fixed at this time. The role involves model integration, validation, deployment, and translating business requirements into technical implementations using data-driven and software-based approaches.