Overview
Remote
Depends on Experience
Full Time
Skills
Snowflake
Azure
AWS
Python
PyTorch
TensorFlow
LangChain
Retrieval-Augmented Generation (RAG)
Model Context Protocol (MCP)
GenAI architecture design
ML/AI model development
API development
Prototyping
Production interfaces
Scalable ML pipelines
CI/CD
Terraform
Jenkins
Healthcare data
Regulated environments
Job Details
Senior Machine Learning Engineer (GenAI / Snowflake)
Location: Remote (EST or CST preferred)
Duration: Full Time
Overview
We are seeking two Senior Machine Learning Engineers to support Generative AI initiatives and advanced AI/ML use cases leveraging the Snowflake Data Cloud. These engineers will design, prototype, and deploy scalable GenAI solutions and interfaces to power next-generation analytics and intelligent applications.
Key Responsibilities
Design and implement GenAI architectures leveraging Snowflake as the primary data platform.
Build retrieval-augmented generation (RAG) workflows and integrate model context protocol (MCP) services for advanced AI applications.
Develop Python-based ML/GenAI models and APIs; create rapid prototypes and production-ready solutions.
Build user-facing interfaces and supporting services for AI/ML features.
Collaborate with cross-functional teams (data engineering, product, cloud) to integrate solutions within Azure and AWS environments.
Establish CI/CD pipelines and infrastructure-as-code practices (Terraform, Jenkins) to automate deployments.
Required Skills & Experience
Strong expertise with Snowflake, including advanced data modeling and optimization.
Hands-on experience with Azure and AWS cloud platforms.
Proficiency in Python for ML/AI development (PyTorch, TensorFlow, LangChain, etc.).
Practical experience with RAG, MCP services, and GenAI architecture design.
Proven ability to build prototypes, production interfaces, and scalable ML pipelines.
Nice-to-Have
Experience with CI/CD, Terraform, and Jenkins for MLOps automation.
Background in healthcare data or regulated environments.
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