Solutions Architect AI/ML
snowflake
Job Description
AS A SOLUTIONS ARCHITECT - AI/ML AT SNOWFLAKE, YOU WILL:
-
Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload
-
Build, deploy and ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements
-
Work hands-on where needed using SQL, Python, and APIs to build POCs that demonstrate implementation techniques and best practices on Snowflake technology for GenAI and ML workloads
-
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
-
Ability and flexibility to travel to work with customers on-site 25% of the time
OUR IDEAL SOLUTION ARCHITECT - AI/ML WILL HAVE:
-
Minimum 10 years experience working with customers in a pre-sales or post-sales technical role
-
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 GCP)
-
Experience with at least one Data Science tool such as Sagemaker, AzureML, Vertex, Dataiku, DataRobot, H2O, and Jupyter Notebooks
-
Experience with Large Language Models, Retrieval and Agentic frameworks
-
Hands-on scripting experience with SQL and at least one of the following; Python, R, Java or Scala.
-
Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn or similar
-
University degree in computer science, engineering, mathematics or related fields, or equivalent experience
BONUS POINTS FOR HAVING:
-
Experience with Generative AI, LLMs and Vector Databases.
-
Experience with Databricks/Apache Spark, including PySpark
-
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.