AI/Machine Learning Engineer SME

Integration Innovation, Inc. (i3); Washington (District of Columbia); Hybrid; USD 200,000 - 350,000; Full time

Job summary

Integration Innovation, Inc. (i3) supports mission-critical data and analytics work for the Defense Intelligence Agency (DIA) through the EDMA effort.

In this hybrid role based in Washington, DC, you will act at the SME level to architect enterprise-ready AI/ML solutions, partner closely with government stakeholders, and help drive responsible-AI and governance aligned to IC and DoD directives. Salary is USD 200,000 - 350,000 per year, with a Secret clearance and TS/SCI eligibility.

Qualifications

• U.S. citizenship required.
• Active Secret clearance with ability to obtain TS/SCI clearance.
• Bachelor’s degree (Master’s preferred) in Computer Science, Engineering, Applied Mathematics, Data Science, or related field.
• Minimum 14 years of progressive experience in AI/ML, data engineering, or advanced analytics.
• Proven experience architecting and deploying enterprise AI/ML systems.
• Deep proficiency in Python and modern ML frameworks, including PyTorch, TensorFlow, and JAX.
• Experience leading technical teams, performing architecture trade studies, and guiding end-to-end ML lifecycle development.
• Strong understanding of secure software engineering, distributed systems, DevSecOps, and containerization.
• Excellent communication skills with senior government stakeholders.

Responsibilities

• Architect enterprise-ready AI/ML solutions spanning model-training pipelines, inference services, feature stores, data-ingestion pathways, and MLOps frameworks aligned to requirements.
• Define and communicate a technical roadmap, translating mission needs into actionable architectures, workstreams, and implementation plans.
• Lead multi-disciplinary engineering efforts, providing technical direction across algorithms, model selection, data strategy, integration, and delivery cadence.
• Oversee sprint planning and technical execution to keep deliverables on track, remove blockers, and ensure engineering artifacts meet enterprise standards.
• Serve as the primary technical interface with government stakeholders, explaining architecture decisions, model behaviors, risk tradeoffs, and recommended solution pathways.
• Establish and enforce best practices for ML engineering, DevSecOps, coding standards, test automation, and model life-cycle governance.
• Run technical reviews and mentor engineers to strengthen capability and maintain alignment with mission outcomes.
• Guide evaluation and adoption of advanced ML tools and patterns, including PyTorch, TensorFlow, and JAX, distributed compute, MLOps platforms, generative-AI modernization patterns, and enterprise-scale data solutions.
• Lead integration of AI capabilities into cloud-native or hybrid architectures, ensuring security, accreditation, and enterprise data-management requirements are met.
• Provide SME-level support for strategic planning, including solution briefs, architecture diagrams, and CONOPS development to support government review panels.
• Champion responsible-AI and governance approaches aligned to IC and DoD directives.

Skills

Python

PyTorch

TensorFlow

JAX

MLOps

DevSecOps

Education

Bachelor’s degree (Master’s preferred) in Computer Science, Engineering, Applied Mathematics, Data Science, or related field

Tools

MLOps platforms

CI/CD

Containerization

Job description

Integration Innovation, Inc. (i3) supports mission-critical data and analytics work for the Defense Intelligence Agency (DIA) through the Enterprise Data Management & Analytics (EDMA) effort. In this hybrid role based in Washington, DC, you will act at the SME level to architect enterprise-ready AI/ML solutions, partner closely with government stakeholders, and help drive responsible-AI and governance aligned to IC and DoD directives.

Salary: USD 200,000 - 350,000 per year.

Security: Active Secret clearance is required, with the ability to obtain and maintain TS/SCI.

What you’ll do

• Architect enterprise-ready AI/ML solutions spanning model-training pipelines, inference services, feature stores, data-ingestion pathways, and MLOps frameworks aligned to requirements.
• Define and communicate a technical roadmap, translating mission needs into actionable architectures, workstreams, and implementation plans.
• Lead multi-disciplinary engineering efforts, providing technical direction across algorithms, model selection, data strategy, integration, and delivery cadence.
• Oversee sprint planning and technical execution to keep deliverables on track, remove blockers, and ensure engineering artifacts meet enterprise standards.
• Serve as the primary technical interface with government stakeholders, explaining architecture decisions, model behaviors, risk tradeoffs, and recommended solution pathways.
• Establish and enforce best practices for ML engineering, DevSecOps, coding standards, test automation, and model life-cycle governance.
• Run technical reviews and mentor engineers to strengthen capability and maintain alignment with mission outcomes.
• Guide evaluation and adoption of advanced ML tools and patterns, including PyTorch, TensorFlow, and JAX, distributed compute, MLOps platforms, generative-AI modernization patterns, and enterprise-scale data solutions.
• Lead integration of AI capabilities into cloud-native or hybrid architectures, ensuring security, accreditation, and enterprise data-management requirements are met.
• Provide SME-level support for strategic planning, including solution briefs, architecture diagrams, and CONOPS development to support government review panels.
• Champion responsible-AI and governance approaches aligned to IC and DoD directives.

What you bring

• U.S. citizenship.
• Active Secret clearance with the ability to obtain and maintain a TS/SCI security clearance.
• Bachelor’s degree (Master’s preferred) in Computer Science, Engineering, Applied Mathematics, Data Science, or a related field.
• Minimum 14 years of progressive experience in AI/ML, data engineering, or advanced analytics.
• Proven experience architecting and deploying enterprise AI/ML systems.
• Deep proficiency in Python and modern ML frameworks, including PyTorch, TensorFlow, and JAX.
• Experience leading technical teams, performing architecture trade studies, and guiding end-to-end ML lifecycle development.
• Strong understanding of secure software engineering, distributed systems, DevSecOps, and containerization.
• Excellent communication skills with the ability to interface with senior government stakeholders.

Technologies

• Python
• PyTorch
• TensorFlow
• JAX
• MLOps
• DevSecOps

Preferred qualifications

• Experience supporting AI/ML projects in government, defense, or intelligence environments.
• Familiarity with Intelligence Community mission needs and data types.
• Exposure to cloud-native development (AWS, Azure, GovCloud).
• Experience building or supporting NLP, computer-vision, generative-AI, or anomaly-detection models.
• Knowledge of MLOps, CI/CD, container orchestration, or distributed training frameworks.