AI/ML Engineer - Cloud & Data Pipelines

SOSi

Chantilly (VA)

Presencial

USD 64.000 - 78.000

Jornada completa

14 días+

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Descripción de la vacante

SOSi in Chantilly, VA is seeking an AI/ML Engineer to design, develop, test, and deploy AI/ML models across domains such as NLP, computer vision, and reinforcement learning. You will preprocess data, build experiments, and deploy scalable cloud-based solutions while ensuring security and compliance.

The role requires an active Top Secret Clearance and hands-on experience with Python, PyTorch, TensorFlow/Keras, cloud services, and model deployment.

Formación

  • Active Top Secret Clearance required.
  • Proficient in Python or R for AI/ML development.
  • Experience with deep learning frameworks (PyTorch, TensorFlow, Keras).
  • Experience with cloud-based AI/ML development and deployment.

Responsabilidades

  • Design and develop AI/ML models and ensembles using Sponsor data.
  • Preprocess and analyze large structured/unstructured data for model training.
  • Collaborate to design experiments to verify model performance.
  • Deploy and maintain AI/ML models in cloud environments with scalability and security.
  • Develop ETL pipelines and SQL configurations for AI/ML apps.
  • Document methods and findings; create visualizations and reports.
  • Provide technical education on AI/ML topics to staff.
  • Provide subject matter expertise to support Sponsor's initiatives.

Conocimientos

Python
PyTorch
TensorFlow/Keras
GitHub
Cloud computing
Model deployment

Herramientas

Flask
Tableau
SQL

Descripción del empleo

SOSi in Chantilly, VA is seeking an AI/ML Engineer to design, develop, test, and deploy AI/ML models across domains such as NLP, computer vision, and reinforcement learning. You will preprocess data, build experiments, and deploy scalable cloud-based solutions while ensuring security and compliance.

The role requires an active Top Secret Clearance and hands-on experience with Python, PyTorch, TensorFlow/Keras, cloud services, and model deployment.

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