Senior AI/ML Engineer **Hybrid

Cube hub

Glendale, WI, United States

3 days ago

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Role details

Contract type

Temporary to permanent

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Compensation

$130,000.0 - $175,000.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Systems Engineering Microsoft Azure Cloud Computing Code Review Continuous Integration Data Infrastructure Monitoring of Systems Python (Programming Language) Machine Learning

+19 more

Scrum Methodology Software Architecture Software Tools Tensorflow Software Deployment Software Engineering Systems Integration Software Organization Google Cloud Pytorch Large Language Models Prompt Engineering Generative AI Scikit Learn Information Technology Process Control Systems Enterprise Integration Machine Learning Operations Data Pipelines

Job description

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Requirements

7+ years of software engineering experience with strong modern software development practices and architecture.
5+ years of hands-on Machine Learning experience, including developing and deploying ML solutions to production.
Strong Python programming skills with experience in AI/ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
Generative AI / LLM experience Building and integrating LLM-powered applications, AI copilots, intelligent recommendations, or natural language interfaces.
Production AI deployment experience Designing scalable inference and deployment architectures across cloud, edge, or on-premises environments.
Cloud experience AWS, Azure, or Google Cloud Platform.
Strong software architecture and integration skills APIs, data pipelines, software development, and production deployment.
AI engineering leadership Establishing AI best practices, mentoring engineers, and using AI tools to improve software development, testing, code reviews, and CI/CD.

Preferred / Nice-to-Have Skills

Retrieval-Augmented Generation (RAG), vector databases, and prompt engineering.
MLOps, model monitoring, AI evaluation, and AI governance.
Edge AI, IoT, or on-premises AI deployment.
Building Automation Systems (BAS), industrial controls, or smart building technologies.
Agile/Scrum experience.
Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related technical field.