Building solutions that augment human intelligence, streamline workflows, and enhance the overall effectiveness of intelligence operations by integrating AI advancements into the existing RAD architecture.
Requirements
- Have experience with the Amazon Web Services (AWS) cloud computing platform and machine learning operations (MLOps) tools for deploying and managing machine learning models at scale.
Responsibilities
- Lead the design and development of AI-driven solutions from conception to deployment, ensuring seamless integration with the existing software architecture. This includes prototyping new models, writing production-quality code, and maintaining existing AI systems.
- Conduct Exploratory Data Analysis (EDA) on diverse datasets (both structured and unstructured) to inform the data model, identify data quality issues, and determine optimal input formats for AI models.
- Develop, train, and evaluate a variety of machine learning models, ensuring they meet performance and reliability requirements. Implement robust testing and validation strategies to ensure models are accurate and unbiased.
- Stay current with the latest advancements in AI and machine learning, continuously seeking opportunities to apply new technologies and methodologies to improve existing systems and solve complex problems.
- Have experience with the Amazon Web Services (AWS) cloud computing platform and machine learning operations (MLOps) tools for deploying and managing machine learning models at scale.
Other
- TS/SCI Full Scope Poly required
- Serve as a key technical liaison, collaborating with cross-functional teams including system engineers, software developers, and domain experts.
- Effectively present and articulate recommended AI approaches, discussing the tradeoffs and implications of different implementations with both technical and non-technical stakeholders.
