Artificial Intelligence & Machine Learning Architect SME
General Dynamics Information Technology7 days ago
Remote, WorldwideStaff+
Base Salary
$195k - $264k/yr
Responsibilities
- Define, document, and maintain scalable, modular AI/ML architecture aligned with enterprise cloud strategy and product requirements.
- Architect and implement end-to-end AI/ML pipelines covering data ingestion, feature engineering, model training, deployment, monitoring, and retraining.
- Apply MLOps practices for continuous integration, delivery, and machine-learning model lifecycle management.
- Design elastic, highly available, cost-efficient multi-tenant and multi-region AI/ML workloads.
- Use infrastructure-as-code tools to provision and manage cloud AI/ML infrastructure in compliance with federal security standards.
- Design and support reusable, secure, performant AI/ML services and APIs for enterprise applications.
- Conduct cloud-based model validation and optimization while supporting responsible AI, fairness, and transparency.
- Maintain architecture documentation and sprint-related technical artifacts.
- Support AI/ML metrics, resource utilization, and performance KPIs in technical dashboards and reports.
- Guide teams in selecting and securely integrating third-party ML tools, frameworks, and SaaS offerings.
Requirements
- BA/BS or equivalent required; relevant MA/MS preferred, with stated experience substitutions for high school, associate, bachelor’s, master’s, and doctoral education.
- 15+ years of specialized information-systems experience required.
- Proven experience architecting and deploying ML workflows in AWS SageMaker, Azure ML, or GCP Vertex AI.
- Hands-on experience with TensorFlow, PyTorch, scikit-learn, XGBoost, or Keras.
- Strong Python programming skills plus Docker and Kubernetes experience for ML workloads.
- Experience with 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.
- Proficiency with Terraform, CDK, or CloudFormation for cloud ML infrastructure automation.
- Experience with multi-tenant distributed systems and cloud-native architecture patterns.
- Relevant AWS Certified Machine Learning–Specialty, Google Professional ML Engineer, or equivalent certification preferred but not required.
- Must pass a background check to obtain Public Trust and must be a US Person, defined as a Green Card holder, US permanent resident alien, refugee, asylee, or US citizen.
Benefits
- Remote work from any location, with less than 10% travel and a 40-hour scheduled work week.
- Medical, dental, vision, and health savings account plan options for US-based employees.
- 401(k) plan with company match and pre-tax and post-tax contribution options.
- Flexible work weeks where possible, paid vacation, sick, personal, holiday, parental, military, bereavement, and jury-duty leave.
- Up to 160 hours of paid family leave in a rolling 12-month period for eligible employees.
- Short- and long-term disability, life, accidental death and dismemberment, personal accident, critical illness, and business travel and accident insurance.
- Career growth resources, internal mobility support, wellness packages, and an innovation-focused workplace culture.