Description
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.
Responsibilities
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.
Requirements
Qualifications
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 SageMaker, 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 DevOps 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.
