AI/ML Engineer SME (TS/SCI with Poly Required)

GCI Incorporated•McLean, VA
•$187,179 - $318,198

About The Position

GCI is seeking an AI/ML Engineer to support customer mission requirements through data analytics and software development. The role focuses on developing, tuning, testing, evaluating, and validating AI/ML models and LLM-based systems, and applying model results to specific use cases. Candidates must be U.S. citizens and hold an active/current TS/SCI clearance with Polygraph.

Requirements

  • U.S. citizenship.
  • Active/current TS/SCI clearance with Polygraph.
  • Professional or academic experience tuning neural networks, such as LLMs, on custom datasets and applying results to specific use cases.
  • Professional or academic experience developing AI/ML models and ensembles, selecting Python libraries and preprocessing actions, performing analysis, and assessing model performance.
  • Professional or academic experience using Python or R.
  • Professional or academic experience with deep learning frameworks such as PyTorch, TensorFlow, or Keras.
  • Professional or academic proficiency with SQL, including common table expressions, set operations, aggregate functions, and nested subqueries.
  • Professional or academic experience with version control systems such as GitHub and Jenkins.
  • Experience leveraging GPUs for accelerated computing.
  • Professional or academic experience testing, evaluating, or validating AI system performance, particularly LLM-based systems.
  • Professional or academic experience designing and executing experiments to test LLM performance against a benchmark.

Nice To Haves

  • Professional or academic experience with the Hugging Face Transformers library and hub.
  • Professional or academic experience developing benchmarks to measure LLM performance.
  • Experience with cloud computing development and architecture.
  • Experience with front-end web development frameworks such as Flask.
  • Experience creating Python machine learning models for text classification and topic modeling using standard machine learning libraries such as scikit-learn or deep learning models.
  • Experience developing applications for semantic search.
  • Professional or academic proficiency with Tableau for producing visualizations and dashboards.
  • Academic or professional experience communicating methodological choices and model results.
  • Experience with verification and validation test benches.
  • Experience with Explainable AI (XAI) techniques.
  • Experience with ONNX (Open Neural Network Exchange).

Responsibilities

  • Tune neural networks, including LLMs, on custom datasets and apply results to specific use cases.
  • Develop AI/ML models and ensembles, selecting appropriate Python libraries and preprocessing methods, conducting analysis, and assessing model performance.
  • Test, evaluate, and validate AI systems, with a focus on LLM-based systems.
  • Design and execute experiments to test LLM performance against benchmarks.
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