AI/ML Architect SME

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Quick Summary

Key Responsibilities

Define, document, and maintain a scalable, modular AI/ML architecture that aligns with enterprise cloud strategy and product requirements for the CMM Program.

Requirements Summary

Skills:Artificial Intelligence (AI), Cloud Development,

Technical Tools

ArchitectConstruction & Real Estate

Regular

Clearance Level Must Currently Possess:

None

Clearance Level Must Be Able to Obtain:

None

BI Full 6C (T4)

Job Family:

Data Science and Data Engineering

Requirements

~1 min read

Education: BA/BS or equivalent required; Master of Arts or Science in related field preferred
Experience: 15+ years of related experience required, with at least 5+ years of recent, demonstrable, hands-on experience architecting and deploying AI/ML workflows in cloud environments utilizing Amazon SageMaker AI, Azure Machine Learning, and/or Google Cloud Vertex AI
Experience may be considered in lieu of degree as follows: HS (19+ years), AA/AS (17+ years), BA/BS (15+ years), MA/MS (13+ years), Doctorate Degree/Ph.D. (12+ years)
Proven success in architecting and deploying AI/ML workflows in cloud environments (Amazon SageMaker AI, Azure Machine Learning, and/or Google Cloud Vertex AI)
Hands-on experience with ML/DL frameworks such as TensorFlow, PyTorch, scikit-learn, XGBoost, or Keras
Strong programming skills in Python, with experience in containerization (Docker) and orchestration (Kubernetes) for ML workloads
Experience with MLOps tools (MLflow, Kubeflow, TFX, Airflow) and CI/CD integration for model deployment
Familiarity with federal data governance, security, and privacy standards, including JISF, NIST 800-53, and FedRAMP
Proficient in using IaC tools such as Terraform, CDK, or CloudFormation to automate cloud ML infrastructure
Experience with multi-tenant, distributed systems, and cloud-native architecture patterns

Artificial Intelligence (AI), Cloud Development, Machine Learning (ML)

None

15 + years of related experience

Job Description:

Seize your opportunity to make a personal impact supporting the Case Management Modernization (CMM) Program. The CMM Program is an initiative to support the Administrative Office of the US Courts (AO) in developing a modern, cloud-based solution to support all 204+ federal courts across the United States.

GDIT is your place to make meaningful contributions to challenging projects and grow a rewarding career. The AI/ML Architect SME will be responsible for defining, designing, deploying, and maintaining the modular AI/ML architecture necessary for the CMM Program. They will architect and implement end-to-end AI/ML pipelines that include data ingestion, feature engineering, model training, deployment, monitoring, and retraining, ensuring the continuous effectiveness and improvement of these solutions. This role provides technical leadership, strategic direction, and tool recommendations for AI/ML architecture to improve the architecture, automation, and delivery of AI/ML products.

We are seeking a candidate with recent, demonstrable, hands-on experience in the AI/ML field to play a key role in the development of this exciting modernization effort that will have far-reaching impacts across the full breadth of the US federal courts system. If you’re interested in this exciting opportunity and would like to grow your AI/ML career with a company that always puts its people at the forefront of everything we do, then we’d love to hear from you!

Responsibilities

~1 min read

→Define, document, and maintain a scalable, modular AI/ML architecture that aligns with enterprise cloud strategy and product requirements for the CMM Program.
→Architect and implement end-to-end AI/ML pipelines including data ingestion, feature engineering, model training, deployment, monitoring, and retraining.
→Integrate MLOps best practices for continuous integration, delivery, and lifecycle management of machine learning models
→Ensure multi-tenant and multi-region AI/ML workloads are elastic, highly available, and cost-efficient
→Leverage Infrastructure-as-Code (IaC) tools to provision and manage cloud-based AI/ML infrastructure in accordance with federal compliance and security standards
→Design and support reusable, secure, and performant AI/ML services and APIs to be consumed by enterprise applications
→Conduct model validation and optimization in cloud environments, ensuring responsible AI practices, fairness, and transparency
→Maintain AI/ML architecture documentation and update artifacts per sprint cycles or as changes occur
→Support the inclusion of AI/ML metrics, resource utilization, and performance KPIs in technical dashboards and reports
→Guide teams on the selection and integration of third-party ML tools, frameworks, or SaaS offerings in a secure and compliant manner

Nice to Have

~1 min read

One or more of the following certifications is preferred but not required.

AWS Certified Machine Learning Engineer – Associate
AWS Certified Machine Learning – Specialty
Microsoft Certified: Azure AI Apps and Agents Developer Associate
Microsoft Certified: Machine Learning Operations Engineer Associate
Google Cloud Professional Machine Learning Engineer

What We Offer

~1 min read

The likely salary range for this position is $170,144 - $212,750. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Scheduled Weekly Hours:

Less than 10%

Remote

Work Location:

Any Location / Remote

Additional Work Locations:

Our benefits package for all US-based employees includes a variety of medical plan options, some with Health Savings Accounts, dental plan options, a vision plan, and a 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match. To encourage work/life balance, GDIT offers employees full flex work weeks where possible and a variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave. GDIT typically provides new employees with 15 days of paid leave per calendar year to be used for vacations, personal business, and illness and an additional 10 paid holidays per year. Paid leave and paid holidays are prorated based on the employee’s date of hire. The GDIT Paid Family Leave program provides a total of up to 160 hours of paid leave in a rolling 12 month period for eligible employees. To ensure our employees are able to protect their income, other offerings such as short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available. We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.

We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50+ countries worldwide, offering leading mission-ready capabilities in AI, cloud, cyber and software development.

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