Snowflake AI/ML Sr. Solutions Architect

Overview

On Site
$70 - $80
Contract - W2
Contract - 12 Month(s)

Skills

Amazon SageMaker
Amazon Web Services
Artificial Intelligence
Cloud Computing
Collaboration
Data Science
Good Clinical Practice
Google Cloud Platform
Java
Jupyter
Knowledge Transfer
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Management
Microsoft Azure
Pandas
Presentations
Product Engineering
Professional Services
PyTorch
Python
SQL
SQL*Plus
Scripting
Snow Flake Schema

Job Details

Job Description AI/ML Architect

The Snowflake AI/ML Architect will serve as a technical expert for AI/ML workloads on Snowflake. This role involves hands-on development, building ML pipelines, supporting customers, and driving best practices across data science and AI engineering teams.

Responsibilities

  • Serve as a subject-matter expert on Snowflake for AI/ML workloads.

  • Provide best practices for Data Science workloads on Snowflake.

  • Build and deploy ML pipelines using Snowflake features and partner tools.

  • Develop POCs using SQL, Python, and Snowflake to demonstrate architecture and best practices.

  • Ensure knowledge transfer for customer teams to self-manage Snowflake solutions.

  • Maintain expertise in competitive AI/ML technologies and position Snowflake effectively.

  • Work with SI partners to deploy Snowflake in customer environments.

  • Troubleshoot customer-specific technical challenges.

  • Support and mentor Professional Services team members.

  • Collaborate with Product, Engineering, and Marketing teams on product improvements.

  • Replatform chatbots to Snowflake Cortex Analyst; integrate Cortex Search; migrate Churn Prediction models.

Requirements

  • 12 14 years of experience in pre-sales or post-sales technical roles.

  • Strong presentation skills for technical and executive audiences.

  • Deep understanding of the full Data Science lifecycle (feature engineering deployment monitoring).

  • Strong MLOps knowledge and model operationalization techniques.

  • Experience with at least one cloud platform: AWS, Azure, or Google Cloud Platform.

  • Experience with Data Science tools: Sagemaker, AzureML, Dataiku, DataRobot, H2O, Jupyter.

  • Hands-on scripting with SQL + Python / Java / Scala.

  • Experience with ML libraries: Pandas, PyTorch, TensorFlow, Scikit-Learn, etc.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

About Softa Ai Solutions