AI/ML Solution Architect

  • Maryland City, MD
  • Posted 3 hours ago | Updated 3 hours ago

Overview

Remote
Hybrid
Depends on Experience
Contract - W2
Contract - Independent
Contract - 12 Month(s)
No Travel Required
Unable to Provide Sponsorship

Skills

Machine Learning (ML)
Artificial Intelligence
Solution Architect
AI/ML
PyTorch
XGBoost
Microsoft Azure
Machine Learning Operations (ML Ops)
Visualization
Microsoft Power BI
Data Science
CPG
MLOps

Job Details

Role - AI/ML Solution Architect 

Location - Remote (Occasional travel to Sailsbury, MD)

 

The candidate should have extensive experience in

 

Qualifications & Experience:

 

·         Bachelor’s or Master’s in Computer Science, Data Science, or related field.

·         15+ years of IT experience, including 5+ years in AI/ML architecture or advanced analytics design.

·         Deep expertise in AI/ML frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, XGBoost.

·         Hands-on knowledge of data platforms: Snowflake, Dataiku, Azure Data Services.

·         Experience defining AI governance, model lifecycle, and compliance standards.

·         Proven ability to lead cross-functional global teams and manage enterprise-scale architecture programs.

·         Strong understanding of CPG domain processes and data-driven decision systems.

 

Preferred Skills:

 

·         Exposure to Snowflake’s advanced AI capabilities (Feature Store, Model Registry, Cortex AI).

·         Experience integrating AI systems with Power BI, Azure Synapse, or custom visualization tools.

·         Understanding of MLOps concepts to effectively partner with operational teams.

·         Defining the AI system's architecture and components, including data pipelines, model selection, and deployment strategies.

·         Collaborating with stakeholders to understand business requirements and align AI solutions with organizational goals.

·         Evaluating and selecting the appropriate AI tools, frameworks, and technologies for the organization's needs. Leverage existing tools wherever possible.

·         Leading and guiding AI engineering teams, including AI Engineers and data scientists, in implementing AI solutions.

·         Ensuring compliance with data privacy regulations, ethical considerations, and best practices in AI development.

·         Overseeing the integration of AI solutions into the existing infrastructure and systems.

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