AI/ML Engineer

Radiance Technologies•Beavercreek, OH

18h•Onsite

About The Position

Radiance Technologies is seeking an experienced AI/ML Engineer to support the National Air and Space Intelligence Center (NASIC). The selected candidate will design, develop, test, and deliver AI/ML components to advance the Intelligence Community’s (IC) ability to characterize complex adversary threats with speed and accuracy. This role involves integrating modernized analytic tools, leveraging relevant data sources, and delivering scalable AI/ML solutions within government cloud architectures. You will design, integrate, and optimize full-lifecycle ML pipelines, from data ingestion and model training to deployment and monitoring, ensuring all solutions meet DoW and Intelligence Community security and compliance standards. You will evaluate emerging technologies, assessing their ability to achieve long-term, reliability, scalability, and mission success. This role requires ability to integrate advanced AI/ML capabilities within secure environments, and a commitment to delivering solutions that adhere to federal security and compliance standards.

Requirements

Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
U.S Citizenship with the ability to obtain and maintain a TS/SCI security clearance.
3 + Years of direct work experience
Proven experience in designing, developing, and deploying AI/ML solutions.
Practical experience with scalable cloud-native applications and event-driven architecture.
Proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Experience with Kubernetes-based platforms and CI/CD pipelines.
Experience collaborating with multidisciplinary technical teams and supporting customer-facing technical engagements

Nice To Haves

Kubernetes certifications (CKA, CKAD)
Active TS/SCI

Responsibilities

Tool Integration: Integrate modernized analytic tools into AI/ML capabilities.
Develop user-friendly interfaces for AI/ML tools.
Incorporate monitoring services, including user-enabled monitoring, model drift detection, and model demand tracking.
Data Requirements: Leverage relevant data sources and types for AI/ML models, including connections to future data sources.
Provide access to datasets necessary for training, testing, and validating AI/ML models.
Document and ensure reproducibility of data preparation steps.
AI/ML Services: Deliver a scalable AI/ML software stack supporting the AI/ML lifecycle across NASIC.
Ensure AI/ML components operate within the architecture, data pipelines, and security frameworks defined by the government.
Design processes for easy sharing of AI/ML models.
AI/ML Models: Design scalable, maintainable, shareable, and adaptable AI/ML models.
Train models using government-approved datasets and document training procedures and evaluation results.
Define retraining triggers, update procedures, and versioning practices to ensure ongoing model accuracy and reliability.
Adhere to industry-accepted AI/ML development principles, including transparency, accountability, and responsible use of data and AI/ML.