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# Lead AI Engineer-Machine Learning

- **Company:** Lincoln Technical Institute
- **Location:** Parsippany-Troy Hills, NJ, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Computer Vision, Confluence, JIRA, Microsoft Azure, Big Data, Data Mining, Data Structures, Github, Python (Programming Language), Machine Learning, Software Architecture, Systems Development Life Cycle, Tensorflow, Azure Machine Learning, High Performance Computing, Pytorch, Large Language Models, Deep Learning, Generative AI, Spark Mllib, Containerization, Scikit Learn, Information Technology, Atlassian Tools, Data Pipelines, Docker, Jenkins
- **Published:** August 16, 2026
- **Apply:** https://www.juju.com/job/00000000gnemsw

## About the Role

+ Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related technical field (advanced degree preferred)

 + 2+ years of experience in ML engineering

 + Proficiency in Python and solid experience with Java or Scala

 + Deep hands-on experience with TensorFlow, PyTorch, Scikit-Learn, or Spark MLlib

 + Experience with cloud platforms (AWS, Azure, or GCP) and their AI/ML services

 + Hands-on experience with CI/CD pipelines and containerization tools including Docker and Kubernetes

 + Experience with SDLC and Agile tools such as Jira, GitHub, Jenkins, and Confluence

 + Expertise in LLMs, Generative AI, Computer Vision, or NLP

 + Strong system design skills with deep understanding of data structures and software architecture

## Description

+ Define the strategic direction for Lincoln Tech's AI/ML technology stack

 + Design and implement scalable, high-performance computing infrastructures for AI/ML and data mining

 + Lead end-to-end lifecycle of AI/ML applications from conceptualization through delivery and support

 + Create and optimize sophisticated AI systems including deep learning, generative AI, and advanced NLP models

 + Architect and maintain efficient data pipelines to clean, preprocess, and manage large datasets

 + Troubleshoot and resolve complex technical issues related to applications and models

 + Communicate complex AI/ML concepts and solutions to non-technical stakeholders and leadership

 + Identify high-value opportunities to leverage AI/ML and define metrics to measure effectiveness


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