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

GCI embodies excellence, integrity and professionalism. The employees supporting our customers deliver unique, high-value mission solutions while effectively leverage the technological expertise of our valued workforce to meet critical mission requirements in the areas of Data Analytics and Software Development, Engineering, Targeting and Analysis, Operations, Training, and Cyber Operations. We maximize opportunities for success by building and maintaining trusted and reliable partnerships with our customers and industry.

At GCI, we solve the hard problems. As an Machine Learning Engineer, a typical day will include the following duties:

• Demonstrated experience tuning neural networks, such as LLMs, on custom data sets and applying results to specific use cases.
• Demonstrated professional or academic experience developing models and ensembles in the AI/ML space, including selecting the best Python libraries for a given task, choosing appropriate pre-processing actions, performing analysis, and assessing model performance.
• Demonstrated professional or academic experience using Python or R.
• Demonstrated professional or academic experience with deep learning frameworks such as PyTorch, Tensorflow, or Keras. (KEY EXPERIENCE FOR CUSTOMER).
• Demonstrated professional or academic experience and proficiency with SQL to include using common table expressions, set operations, aggregated functions and nested subqueries.
• Demonstrated professional or academic experience with version control systems such as Github and Jenkins.
• Demonstrated experience leveraging GPUs for accelerated computing. (KEY EXPERIENCE FOR CUSTOMER).
• Demonstrated professional experience or academic experience in testing, evaluating, or validating the performance of AI systems with a focus on LLM-based systems (KEY EXPERIENCE FOR CUSTOMER).
• Demonstrated professional or academic experience in experiment design and execution to test the performance of LLMs against a benchmark. 

• Demonstrated professional or academic experience with the HuggingFace Transformers library and hub.
• Demonstrated professional or academic experience in the development of benchmarks to measure LLM performance. (KEY EXPERIENCE FOR CUSTOMER).
• Demonstrated experience with cloud computing development and architecture.
• Demonstrated experience with front-end web development frameworks such as Flask.
• Demonstrated experience creating machine learning models that conduct text classification and topic modeling in Python using standard machine learning (SciKit Learn-) or deep learning models.
• Demonstrated experience developing applications for semantic search.
• Demonstrated professional or academic experience with proficiency with Tableau to produce visualizations and dashboards.
• Demonstrated academic or professional experience communicating methodological choices and model results.
• Demonstrated experience with verification and validation test benches.
• Demonstrated experience with Explainable AI (XAI) techniques.
• Demonstrated experience with ONNX (Open Neural Net Exchange).

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans