Lead AI/ML Architect

Chenega Corporation•UNAVAILABLE, Washington, DC

1d•Remote

About The Position

The Lead AI/ML Architect is responsible for identifying, designing, and governing Artificial Intelligence (AI) and Machine Learning (ML) solutions that enhance the GSAFleet.gov platform and support GSA Fleet's strategic objective of workforce augmentation, automation, analytics, and data-driven decision-making. The role is a member of the Program Management Team and serves as the senior advisor for AI strategy, architecture, and implementation.

Requirements

Bachelor’s Degree in a related field
5+ years of progressively responsible experience designing, developing, and deploying enterprise-level Artificial Intelligence/Machine Learning (AI/ML) solutions.
Must be able to undergo a Tier 2S Investigation and receive a favorable investigation/adjudication outcome
Successfully pass background and drug screening

Nice To Haves

Delivered AI/ML for vehicle utilization, maintenance, telematics, transaction anomalies, or fleet demand forecasting
Relevant cloud AI/ML credentials (Certified Machine Learning Engineer – Associate, AWS Certified Solutions Architect – Associate, AWS Certified Solutions Architect – Professional)
Proven ability to lead and drive multiple parallel, complex customer AI/ML solution-design efforts from inception through solution recommendation/proposal.
Demonstrated expertise conducting comprehensive business and technical discovery with diverse customers to identify strategic needs and high-impact opportunities for AI/ML adoption.
Demonstrated experience identifying, proposing, and architecting novel AI/ML solutions, architectures, and use cases, including areas such as predictive modeling, natural language processing, computer vision, and generative AI.
Demonstrated ability to present complex AI/ML solutions and data-driven recommendations to senior technical and business stakeholders, combining business acumen with technical expertise and connecting proposed solutions to measurable program outcomes.
Demonstrated ability to develop robust, defensible, data-driven recommendations for AI/ML engagements, including proactively identifying and mitigating critical dependencies, risks, and gaps such as data quality and model governance.
Demonstrated experience designing interface standards, quality assurance standards, and performance standards for highly available and reliable AI/ML systems.
Demonstrated experience conducting rigorous cost-benefit analyses and Total Cost of Ownership (TCO) assessments for modern enterprise AI/ML systems.
Deep analytical knowledge of AI/ML technologies, platforms, and frameworks, such as TensorFlow, PyTorch, AWS SageMaker, Azure Machine Learning, Google Vertex AI, or comparable technologies.
Demonstrated ability to evaluate AI/ML technology alternatives and make strategic, data-driven recommendations regarding technology selection and optimal implementation

Responsibilities

Discover and prioritize Fleet AI/ML use cases for analytics, intelligent workflows, automation, and workforce support.
Evaluate each use case for data readiness, mission value, feasibility, dependencies, risk, and operating cost.
Design model, data pipeline, interface, monitoring, quality, governance, security, and deployment requirements.
Present solution options and cost-benefit recommendations to GSA IT and Fleet business stakeholders.
Coordinate with the Data Architect, Solution Architect, ISSO, and product teams to implement approved capabilities.
Measure deployed solution performance and business outcomes and recommend refinements.
Other duties as assigned