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# AI/ML Engineer (hybrid, minimal travel)

- **Company:** Vitaver & Associates, Inc.
- **Location:** Miami, FL, United States (Remote available)
- **Experience:** Expert
- **Salary:** $165,000.0
- **Contract:** Contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, ARM Architecture, Cloud Engineering, Data Sharing, Python (Programming Language), Machine Learning, Software Deployment, Software Engineering, Large Language Models, Snowflake, Multi-Agent Systems, Prompt Engineering, AWS ECS, Scikit Learn, Information Technology, Machine Learning Operations, Api Design
- **Published:** September 5, 2026
- **Apply:** https://www.careerjet.com/job/us90206eb81409c0ba33955d9ef1102fb8/eaa

## About the Role

* Experience in AI/ML engineering, data science, or a related software engineering discipline (5+ years);
 * Experience building, deploying, and monitoring production AI or ML systems, including multi-agent system design and orchestration at scale;
 * Experience with cloud-based AI platforms;
 * Experience with Snowflake technical stack, including Cortex, Snowpark, data sharing, and S3-based data export patterns;
 * Experience with Amazon Bedrock, AWS SageMaker, and ECS for AI/ML workloads;
 * Experience with agentic frameworks such as Snowflake Intelligence, LangGraph, LangChain, AutoGen, or CrewAI;
 * Experience with Python, including ML libraries and API development;
 * Experience with LLM orchestration, prompt engineering, and RAG patterns;
 * Experience with CI/CD pipelines and MLOps best practices;
 * Experience with responsible AI principles, model governance, and data privacy standards; AWS certification (ML Specialty, Solutions Architect, or Developer) is a plus;
 * Bachelor's degree in Computer Science, Data Science, or a related field.

Preferred:

 * Experience in a corporate or enterprise environment;
 * Master's degree in Machine Learning, AI, Computer Science, or Statistics.

## Description

* Design, develop, deploy, and monitor AI solutions, primarily within Snowflake using Cortex and Snowpark capabilities;
 * Ingest business requirements and translate process flows into production-ready AI use cases;
 * Support and monitor an existing AWS ECS container-based AI project as it continues to evolve;
 * Build and scale production-grade AI products, multi-agent systems, machine learning models, and enterprise automation solutions;
 * Own the full lifecycle of AI solutions, from concept and experimentation through production deployment and optimization;
 * Help shape a growing AI engineering function from the ground up, influencing architecture, technology standards, and deployment patterns;
 * Collaborate closely with data, analytics, and business leaders to translate business challenges into scalable AI solutions.


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