Title: Machine Learning Engineer
Location: McLean, VA
*Clearance: *Active TS/SCI w/ Polygraph needed to apply *
Company Overview:
Cornerstone Defense is the Employer of Choice within the Intelligence, Defense, and Space communities of the U.S. Government. Realizing early on that our most prized assets are our employees, we continually focus our attention on improving the overall work/life experience they have supporting the mission. Our Team is pushed every day to use their industry leading knowledge to provide end-to-end solutions to combat our nation’s toughest and most secure problems. If you are looking for a place to not only be professionally challenged, but encouraged and supported by a company that cares, don’t look any further than Cornerstone Defense.
| Customer Labor Category: Machine Learning Engineer – – Customer Skill Level(s): Subject Matter Expert Position Description: REQUIRED SKILLS AND DEMONSTRATED EXPERIENCE • 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) HIGHLY DESIRED SKILLS AND DEMONSTRATED EXPERIENCE • Demonstrated professional or academic experience with the HuggingFace Transformers library and hub. • 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 and 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). |