Machine Learning/AI Engineer (Lead)

Role : Machine Learning Lead/AI Engineer (Lead)

Location :: Alpharetta GA (OR) Oakland Bay area , CA (weekly one day in office)

Exp Req : 15-20 Yrs Max

Visa : USC/GC/GC EAD

• **Need Strong experience in Snowflake , Azure Machine Learning, MLOps

Role Summary

We are seeking a hands-on Machine Learning / AI Engineer to lead the adoption, governance, and productionization of ML and AI solutions within a leading Dental Insurance organization. This role will serve as the technical advisor and mentor for citizen data scientists and ML practitioners, establishing best practices, scalable architectures, and operational frameworks for AI/ML solutions.

The ideal candidate has strong experience with Snowflake, Azure Machine Learning, MLOps, and enterprise AI platforms.

Key Responsibilities

Define and implement enterprise best practices for Machine Learning, Generative AI, and MLOps.

Partner with business, product, data engineering, and analytics teams to identify and prioritize AI/ML use cases.

Guide citizen data scientists and analysts in developing production-ready ML solutions.

Design, build, and operationalize ML models and AI solutions using Snowflake and Azure ML.

Establish model governance, monitoring, versioning, explainability, and model lifecycle management processes.

Collaborate with Data Engineering teams to build scalable feature engineering and data pipelines.

Evaluate and recommend AI/ML tools, frameworks, and architectural patterns.

Support deployment and operationalization of predictive analytics, NLP, GenAI, and intelligent automation use cases.

Ensure compliance with security, privacy, and regulatory requirements in a healthcare/insurance environment.

Required Qualifications

7+ years of experience in Data Science, Machine Learning, or AI Engineering.

Strong hands-on experience with Azure Machine Learning and MLOps.

Experience working with Snowflake, including Snowpark, ML capabilities, and AI features.

Proficiency in Python and ML frameworks such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.

Experience deploying and monitoring ML models in production environments.

Strong understanding of feature engineering, model governance, and model lifecycle management.

Excellent communication and stakeholder management skills.

Preferred Qualifications

Experience in Healthcare or Insurance domains (Dental Insurance preferred).

Experience with Generative AI, LLMs, RAG architectures, and AI governance.

Familiarity with Azure OpenAI, Snowflake Cortex, and enterprise AI platforms.

Regards,

Mike Smith

mike.smith@vbize.net