Solutions Architect - AI/ML

Summary

Join the Snowflake team to build the future of data. We are looking for people with strong backgrounds in data science and cloud architecture to join our AI/ML Workload Services team.

Requirements

• 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

Responsibilities

• 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

Preferred Qualifications

• 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