Engineer Jobs

About The Position

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.