below marketmost similar roles pay hereabove market
This role pays more than
78%
of similar roles. Most pay
$172,462–$234,625
— the blue band above.
At the midpoint, this role pays about
$240k
versus about
$204k
for comparable roles.
Based on 240 similar postings.
Employer
About General Dynamics
General Dynamics is a global aerospace and defense company offering a broad portfolio of products and services in business aviation, ship construction, land combat vehicles, and information technology. It serves customers in the U.S. government, allied governments, and a diverse array of commercial markets.
General Dynamics currently has
1377 open roles
on FindRole.
Listed pay typically runs
$124,093–$150,385
across 1184 roles with salary data.
The AI/ML Technical Architect Lead joins the technical solutions team to support the Centers for Medicare and Medicaid Services. In this hands-on development role, you will architect, develop, and operationalize AI/ML capabilities to enhance decision support and operational readiness. You will design and deploy scalable models, algorithms, and automation frameworks while overseeing data engineering pipelines and MLOps practices. Key responsibilities include integrating solutions into secure enterprise environments, ensuring compliance with cybersecurity and data governance standards, and managing model validation and bias mitigation. You will utilize programming languages like Python, R, and Java alongside frameworks such as TensorFlow or PyTorch, specifically within AWS SageMaker. The role involves building functional prototypes using Retrieval-Augmented Generation and agentic AI technologies to solve complex organizational productivity and automation challenges.
Design and deploy scalable AI/ML models and algorithms to enhance organizational productivity and decision-making.
Lead the development of predictive analytics, automation frameworks, and intelligent decision-support systems.
Integrate AI solutions into secure enterprise and tactical environments while ensuring compliance with cybersecurity standards.
Oversee data engineering pipelines and manage the full model lifecycle using MLOps practices.
Develop and maintain practices for model validation, explainability, and bias mitigation.
Drive AI security risk management by assessing threats and producing required ATO and incident response documentation.
Transition experimental or prototype AI capabilities into operational production systems.
Mentor junior engineers and provide technical leadership across cross-functional teams.
What we're looking for
Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field (Master's or PhD preferred).
10+ years of progressive experience in AI/ML, data science, software engineering, or related advanced analytics disciplines.
5+ years of hands-on experience designing, developing, and deploying AI/ML solutions in production environments.
Proficiency in programming languages such as Python, R, and/or Java.
Deep understanding of machine learning frameworks such as TensorFlow or PyTorch, preferably implemented within AWS SageMaker (preferred).
Experience developing AI products or functional prototypes using Retrieval-Augmented Generation (RAG) and agentic AI technologies.
Experience working with cloud computing platforms (AWS preferred; Azure or Google Cloud acceptable) and using AI services such as AWS Bedrock, Azure AI Foundry, or Google Vertex AI.
Ability to obtain a Public Trust clearance and have lived in the United States at least three out of the last five years.
Python
SQL
Snowflake
Azure
Databricks
PostgreSQL
Power BI
Data Engineering
data-integration
Data Observability
Lakehouse
Ontology Mapping
machine-learning
Data Quality
Telemetry
Data Contracts
Schema Evolution
Performance Testing