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.