Senior AI-ML Engineer

Overview

Job Summary
We are seeking a Senior-level AI/ML Engineer to design, develop, and deploy advanced artificial intelligence and machine learning solutions in support of mission-critical government programs. This role requires deep expertise in architecting scalable, high-performing AI systems on cloud platforms, integrating AI/ML models with enterprise systems, and leveraging big data processing to drive intelligent outcomes.

The ideal candidate brings hands-on experience with cloud-based AI platforms, advanced machine learning techniques, and Responsible AI practices, and thrives in a collaborative, fast-paced technical environment.

• Design, develop, and deploy scalable AI/ML solutions on cloud platforms.
• Architect high-performing AI systems for predictive analytics, natural language processing, and computer vision applications.
• Implement and manage AI/ML pipelines and tooling in cloud environments.
• Integrate AI/ML models with existing enterprise and cloud-based systems to ensure seamless operations.
• Apply advanced machine learning techniques and big data processing to enhance model performance.
• Adhere to Responsible AI (RAI) policies and develop metrics to evaluate AI solution effectiveness.
• Collaborate with cross-functional teams to identify opportunities for AI/ML adoption and integration.
• Stay current with emerging AI/ML technologies, tools, and industry best practices.

• Required
• Active TS/SCI clearance.
• Bachelor’s or Master’s degree in Computer Science, Information Technology, Management Information Systems, or a related STEM field.
• 6–10 years of experience in AI/ML development and deployment.
• Proven experience in designing and implementing AI/ML solutions and cloud-based pipeline tools.
• Advanced expertise in architecting scalable, high-performing AI systems for NLP, computer vision, and predictive analytics.
• Extensive experience with cloud AI platforms such as Azure Machine Learning, AWS Sage Maker, or Google Vertex AI.
• Strong background in big data processing and advanced ML techniques.
• Demonstrated ability to integrate AI/ML models with enterprise systems and cloud environments.
• Deep proficiency in machine learning programming languages such as Python or R.
• In-depth knowledge of AI cloud tools and capabilities.
• Understanding of Responsible AI (RAI) principles, metrics, and evaluation methodologies.
• Relevant certifications such as:
• Azure Solutions Architect
• AI Engineer Associate (or equivalent)
• AWS Certified Machine Learning
• Security+
• Desired
• Experience with containerization and orchestration technologies (Docker, Kubernetes).
• Knowledge of Dev Ops practices and CI/CD pipelines.
• Familiarity with data visualization tools and techniques.
• Strong problem-solving skills and ability to perform effectively in a fast-paced environment.