Snowflake SOLUTIONS ARCHITECT – AI/ML 

Singapore, Singapore 

334018936

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, Java and/or Scala 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

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 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

University degree in computer science, engineering, mathematics or related fields, or equivalent experience

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