Nexwave

Machine Learning / AI Engineer (Lead) with MLOps

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning / AI Engineer (Lead) with MLOps, requiring 15-20 years of experience, based in Alpharetta, GA or Bay Area, CA. Pay rate is unspecified. Key skills include Azure ML, Snowflake, and experience in healthcare or insurance.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
July 10, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
San Francisco Bay Area
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🧠 - Skills detailed
#Data Science #ML (Machine Learning) #Compliance #Data Engineering #Deployment #AI (Artificial Intelligence) #Security #Snowflake #NLP (Natural Language Processing) #Scala #PyTorch #TensorFlow #Azure #Azure Machine Learning #Data Pipeline #Monitoring #Python #Snowpark #Automation
Role description
Role : Machine Learning / AI Engineer (Lead) Location :: Alpharetta GA or Bay area , CA (1 day in office) Exp Req : 15-20 Yrs Max 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.