Job 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
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Design, develop, and deploy scalable AI/ML solutions on cloud platforms.
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Architect high-performing AI systems for predictive analytics, natural language processing, and computer vision applications.
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Implement and manage AI/ML pipelines and tooling in cloud environments.
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Integrate AI/ML models with existing enterprise and cloud-based systems to ensure seamless operations.
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Apply advanced machine learning techniques and big data processing to enhance model performance.
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Adhere to Responsible AI (RAI) policies and develop metrics to evaluate AI solution effectiveness.
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Collaborate with cross-functional teams to identify opportunities for AI/ML adoption and integration.
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Stay current with emerging AI/ML technologies, tools, and industry best practices.
Qualifications
Required
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Active TS/SCI clearance.
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Bachelors or Masters degree in Computer Science, Information Technology, Management Information Systems, or a related STEM field.
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6–10 years of experience in AI/ML development and deployment.
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Proven experience in designing and implementing AI/ML solutions and cloud-based pipeline tools.
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Advanced expertise in architecting scalable, high-performing AI systems for NLP, computer vision, and predictive analytics.
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Extensive experience with cloud AI platforms such as Azure Machine Learning, AWS SageMaker, or Google Vertex AI.
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Strong background in big data processing and advanced ML techniques.
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Demonstrated ability to integrate AI/ML models with enterprise systems and cloud environments.
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Deep proficiency in machine learning programming languages such as Python or R.
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In-depth knowledge of AI cloud tools and capabilities.
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Understanding of Responsible AI (RAI) principles, metrics, and evaluation methodologies.
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Relevant certifications such as:
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Azure Solutions Architect
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AI Engineer Associate (or equivalent)
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AWS Certified Machine Learning
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Security+
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Desired
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Experience with containerization and orchestration technologies (Docker, Kubernetes).
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Knowledge of DevOps practices and CI/CD pipelines.
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Familiarity with data visualization tools and techniques.
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Strong problem-solving skills and ability to perform effectively in a fast-paced environment.