What are the responsibilities and job description for the AI/ML Engineer position at Twinn Intelligence Group?
TWINN is seeking a AI Engineer with machine learning experience to join their team in McLean, Va. Position requires that you are US Citizen and have a clearance level of TS/SCI and top Poly.
REQUIRED SKILLS AND DEMONSTRATED EXPERIENCE
***TS/SCI with POLY***
• 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.
• 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.
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).
REQUIRED SKILLS AND DEMONSTRATED EXPERIENCE
***TS/SCI with POLY***
• 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.
• 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.
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).
