AI/ML Solutions Architect

Radiance is seeking a highly skilled AI/ML Solutions Architect to lead the design, development, and deployment of advanced artificial intelligence and machine learning solutions supporting mission-critical government and national security programs. In this role, you will work closely with cross-functional teams including data scientists, software engineers, cloud architects, and mission stakeholders to translate complex operational requirements into scalable, secure, and high-performance AI/ML architectures.

The ideal candidate combines technical depth with a strategic mindset, enabling them to architect and guide -end-to-end AI/ML solutions that operate in classified cloud environments (AWS C2S, Azure Government Secret). You will design, integrate, and optimize full-lifecycle ML pipelines, from data ingestion and model training to deployment and monitoring, ensuring all solutions meet DoD and Intelligence Community security and compliance standards.

You will evaluate emerging technologies, develop technical roadmaps, and ensure deployed systems achieve long-term, reliability, scalability, and mission success. This role requires strong communication skills to convey complex technical concepts to diverse audiences, the ability to integrate advanced AI/ML capabilities within secure environments, and a commitment to delivering solutions that adhere to federal security and compliance standards.

Required Experience:

• Bachelor's Degree in Computer Science, Engineering, Physics, Statistics, Mathematics or a related field
• 5+ years of professional experience in AI/ML engineering, data science, machine learning operations (MLOps), in cloud environments.
• U.S. citizenship and ability to obtain/maintain TS/SCI security clearance
• Demonstrated experience designing end-to-end AI/ML pipelines operating in classified environments (AWS C2S, Azure Government Secret)
• Demonstrated experience architecting, implementing and operationalizing ML models and data pipelines in production environments across air-gapped and hybrid infrastructures.
• Hands-on experience with at least one major cloud-based AI/ML platform ( Azure Machine Learning, AWS SageMaker, or Kubeflow on Kubernetes)
• Proven background working with structured and unstructured data, feature engineering, and model lifecycle management.
• Experience collaborating with multidisciplinary technical teams and supporting customer-facing technical engagements.

Required Skills:

• Deep understanding of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and data processing tools (Spark, Pandas, Kafka).
• Strong grasp of AI/ML architecture patterns, MLOps principles, including CI/CD for ML, model deployment, monitoring, and governance.
• Proficiency in Python for AI/ML development; familiarity with languages such as Java, Go, or C++ is a plus.
• Expertise with cloud-native and container technologies: Kubernetes, Docker, serverless architectures, and understanding of cloud security and zero trust best practices.
• Ability to translate mission needs into technical requirements and architect end-to-end AI/ML solutions.
• Excellent written and verbal communication skills, with proven ability to present complex AI/ML concepts to senior stakeholders

Desired Skills:

• Active TS/SCI or higher clearance.
• Professional certifications such as
• AWS Certified Solutions Architect / Machine Learning - Specialty
• Azure Solutions Architect / Azure AI Engineer
• CompTIA Security+, CISSP, or equivalent.
• Experience with advanced ML domains, such as federated learning, reinforcement learning, LLM fine-tuning, vector databases, or retrieval-augmented generation (RAG).
• Familiarity with DoD and Intelligence Community data environments, including security constraints and RMF accreditation processes,.
• Understanding of zero-trust architectures, secure data enclaves, and cross-domain solutions.
• Experience with model interpretability, bias mitigation, and Responsible AI best practices

EOE/Minorities/Females/Vet/Disabled