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# AI/ML Engineer (Active TS/SCI )

- **Company:** Rackner, Inc.
- **Location:** United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cloud Computing, Information Engineering, High-Level Architecture, Machine Learning, Metadata Standards, Object Detection, Tensorflow, Management of Software Versions, Feature Engineering, Pytorch, Large Language Models, Deep Learning, Convolutional Neural Networks, HuggingFace, Machine Learning Operations, GPT, Devsecops, Recurrent Neural Networks
- **Published:** May 20, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=e3a510ea159281c2

## About the Role

Do you have experience in Model training?, * Strong proficiency in designing and implementing model architectures, including:
*

 + Convolutional Neural Networks (CNNs)
 + Recurrent Neural Networks (RNNs)
 + Transformer-based architectures
 + Large Language Models (LLMs)
 + Object Detection models (e.g., YOLO, Faster R-CNN)
 * Hands-on experience with:
*

 + PyTorch and/or TensorFlow
 + Hugging Face, Ollama, or similar frameworks
 * Experience with data engineering concepts, including:
*

 + Feature engineering and dataset preparation
 + Data versioning tools (e.g., lakeFS)
 + Metadata standards such as STAC
 * Ability to create clear and effective AI/ML training runbooks
 * Strong problem-solving skills and ability to work in a collaborative environment, * Experience deploying models in cloud-native environments
 * Familiarity with DevSecOps practices
 * Experience working with large-scale or federal datasets
 * Understanding of MLOps principles and pipelines

## Description

Rackner is seeking a highly skilled AI/ML Engineer to design, develop, and deploy advanced machine learning solutions that support mission-critical systems. This role will focus on building scalable models, developing training pipelines, and collaborating with cross-functional teams to deliver impactful AI-driven solutions., * Design, develop, and implement machine learning and deep learning models

 * Build and optimize model architectures including CNNs, RNNs, and transformer-based models
 * Develop and deploy Large Language Models (LLMs) and object detection systems (e.g., YOLO, Faster R-CNN)
 * Perform feature engineering and prepare high-quality datasets for training and evaluation
 * Create and maintain AI/ML training runbooks and documentation
 * Collaborate with data engineers and software teams to integrate models into production systems
 * Ensure reproducibility through data versioning and metadata standards
 * Continuously evaluate and improve model performance and scalability


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