TS/SCI AI/ML Engineer

Insight Global
Beavercreek, OH, United States
2 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
4 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Application Performance Management Computer Vision Cloud Computing Nvidia CUDA Python (Programming Language) Machine Learning Tensorflow Pytorch Large Language Models Model Validation Gpu Programming
+3 more
Real Time Data Machine Learning Operations Stream Processing

Job description

An employer in the Dayton, Ohio, area is seeking a TS/SCI AI/ML Engineer for a contract-to-hire opportunity. This individual will be responsible for designing, developing, and deploying advanced artificial intelligence and machine learning solutions that support critical national security and intelligence missions. The role includes building and implementing applications leveraging technologies such as NLP, Large Language Models (LLMs), generative AI, and computer vision to automate analysis and enhance decision-making. This engineer will collaborate closely with software engineers, analysts, and mission stakeholders to modernize existing workflows and deliver scalable, production-ready AI capabilities. Additional responsibilities include optimizing application performance using GPU technologies such as CUDA and RAPIDS, as well as developing real-time data processing solutions that integrate streaming and near-real-time data feeds into operational environments. The ideal candidate will

Requirements

possess an active TS/SCI clearance, be willing to obtain a CI Polygraph, and be able to work onsite five days per week., Active TS/SCI security clearance (willing to take a CI Polygraph) Bachelor’s Degree (STEM preferred) 4+ years of experience developing AI/ML capabilities Experience with devising AI-agent planning, reasoning, and execution loops Experience with Python-based ML frameworks (PyTorch or TensorFlow) Experience with demonstrating statically-sound model evaluation and AI quality metrics Experience building, deploying, and operating production ML models using either supervised, unsupervised, or anomaly detection efforts Master’s Degree Experience in GPU programming (RAPIDS or CUDA) Cloud experience ML engineering and MLOps experience

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