Overview
Full Time
Accepts corp to corp applications
Contract - W2
Contract - 12 Month(s)
Skills
Information Technology
Databricks
Snowflake
Scripting
Data Science
Marketing
Data Pipelines
Amazon Web Services
Microsoft Azure
Product Management
Pandas
Artificial Intelligence
Databases
Large Language Models
Python (Programming Language)
Pytorch
Java (Programming Language)
SQL Databases
Enterprise Software Applications
Extract Transform Load (ETL)
Consulting
Sales
Apache Spark
Manufacturing
Retail Commerce
Public Cloud Computing Platform
Scikit Learn
Tensorflow
Demonstration Skills
ARM Architecture
Dataiku
Feature Engineering
Jupyter Notebook
Knowledge of Mathematics
Machine Learning Operations
Presales
Professional Services
Whiteboard Programming
Job Details
Snowflake AI/ML Sr Solutions Architect 12-14+ Needed
100% Remote
Must Have Skills: Cortex Analyst, Cortex Search, Snowflake Intelligence
JOB DESCRIPTION
SNOWFLAKE AI/ML ARCHITECT
Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload.
Provide customers with best practices and advise as it relates to Data Science workloads on Snowflake
Build and deploy ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements.
Work hands-on where needed using SQL, Python, to build POCs that demonstrate implementation techniques and best practices on Snowflake technology within the Data Science workload.
Follow best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own
Maintain deep understanding of competitive and complementary technologies and vendors within the AI/ML space, and how to position Snowflake in relation to them
Work with System Integrator consultants at a deep technical level to successfully position and deploy Snowflake in customer environments
Provide guidance on how to resolve customer-specific technical challenges.
Support other members of the Professional Services team develop their expertise.
Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake's products and marketing.
SNOWFLAKE AI/ML ARCHITECT
Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload.
Provide customers with best practices and advise as it relates to Data Science workloads on Snowflake
Build and deploy ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements.
Work hands-on where needed using SQL, Python, to build POCs that demonstrate implementation techniques and best practices on Snowflake technology within the Data Science workload.
Follow best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own
Maintain deep understanding of competitive and complementary technologies and vendors within the AI/ML space, and how to position Snowflake in relation to them
Work with System Integrator consultants at a deep technical level to successfully position and deploy Snowflake in customer environments
Provide guidance on how to resolve customer-specific technical challenges.
Support other members of the Professional Services team develop their expertise.
Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake's products and marketing.
REQUIREMENTS
University degree in data science, computer science, engineering, mathematics or related fields, or equivalent experience.
12-14 years experience working with customers in a pre-sales or post-sales technical role.
Outstanding skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
Thorough understanding of the complete Data Science life-cycle including feature engineering, model development, model deployment and model management.
Strong understanding of MLOps, coupled with technologies and methodologies for deploying and monitoring models.
Experience and understanding of at least one public cloud platform (AWS, Azure or Google Cloud Platform).
Experience with at least one Data Science tool such as AWS Sagemaker, AzureML, Dataiku, Datarobot, H2O, and Jupyter Notebooks.
Hands-on scripting experience with SQL and at least one of the following; Python, Java or Scala.
Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn or similar.
BONUS POINTS FOR HAVING :
Experience with GenerativeAI, LLMs and Vector Databases.
Experience with Databricks/Apache Spark.
Experience implementing data pipelines using ETL tools.
Experience working in a Data Science role.
Proven success at enterprise software.
Vertical expertise in a core vertical such as FSI, Retail, Manufacturing, etc.
University degree in data science, computer science, engineering, mathematics or related fields, or equivalent experience.
12-14 years experience working with customers in a pre-sales or post-sales technical role.
Outstanding skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
Thorough understanding of the complete Data Science life-cycle including feature engineering, model development, model deployment and model management.
Strong understanding of MLOps, coupled with technologies and methodologies for deploying and monitoring models.
Experience and understanding of at least one public cloud platform (AWS, Azure or Google Cloud Platform).
Experience with at least one Data Science tool such as AWS Sagemaker, AzureML, Dataiku, Datarobot, H2O, and Jupyter Notebooks.
Hands-on scripting experience with SQL and at least one of the following; Python, Java or Scala.
Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn or similar.
BONUS POINTS FOR HAVING :
Experience with GenerativeAI, LLMs and Vector Databases.
Experience with Databricks/Apache Spark.
Experience implementing data pipelines using ETL tools.
Experience working in a Data Science role.
Proven success at enterprise software.
Vertical expertise in a core vertical such as FSI, Retail, Manufacturing, 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.