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# Artificial Intelligence Machine Learning 2 - Telework 16 hrs

- **Company:** ASCENT SERVICES GROUP LLC
- **Location:** Hanover, MD, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** C (Programming Language), Java (Programming Language), Artificial Intelligence, R (Programming Language), Python (Programming Language), Machine Learning, Tensorflow, Verification and Validation (Software), Pytorch, Knowledge Representation, Scikit Learn, Information Technology, Data Pipelines
- **Published:** October 31, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9277013/artificial-intelligence-machine-learning-2-telework-16-hrs

## About the Role

* Experience with machine language frameworks (e.g. Pytorch, TensorFlow)
 * Experience in working with various ML libraries and packages
 * Oversee test and evaluation of AI and ML algorithms through an iterative design process to meet verification and validation requirements
 * Research and implement a broad range of AI and ML algorithms and tools
 * Design or select appropriate data and knowledge representation methods
 * Must meet the Labor Category requirements, contact staffing@ascendantinnovations.com for details.

DESIRED SKILLS:

 * Expert knowledge of Python, Java, C, and R
 * Must meet the Labor Category requirements, contact staffing@ascendantinnovations.com for details., * PhD or Master's degree in Computer Science or related discipline from an accredited college or university, plus two (2) years of experience in programs and contracts of similar scope, type, and complexity.

OR

 * Bachelor's degree in Computer Science or related discipline from an accredited college or university, plus seven (7) years of experience in programs and contracts of similar scope, type, and complexity.

## Description

Ascendant Innovations Corp is seeking an AI/ML Engineer to design, deploy, and optimize scalable machine learning models to solve complex business challenges and meet customer requirements. The candidate will manage the complete model lifecycle-from architecture and data pipeline integration to training, monitoring, and iterative retraining based on system feedback.