Senior Architect, Machine Learning Field CTO

We’re at the forefront of the data revolution, committed to building the world’s greatest data and applications platform. Our ‘get it done’ culture allows everyone at Snowflake to have an equal opportunity to innovate on new ideas, create work with a lasting impact, and excel in a culture of collaboration.

Our Sales Engineering organization is seeking a Senior Architect, AI/ML Field CTO who can provide leadership to our customers building machine learning and generative AI solutions on the Snowflake AI Data Cloud.

As a Senior Architect focused on AI/ML you must share our passion and vision in helping our customers and partners drive faster time to value through Snowflake’s AI Data Cloud, thrive in a dynamic environment, and have the flexibility and willingness to jump in and get things done. You are equally comfortable in both a business and technical context, interacting with executives and talking shop with technical audiences.

IN THIS ROLE YOU WILL GET TO:

• Apply your data science architecture expertise while presenting Snowflake technology and vision to executives and technical stakeholders at strategic prospects, customers, and partners.
• Work with Snowflake account teams to help customers scope AI and ML projects, execute technical evaluations, and architect production grade solutions.
• Collaborate closely with our Product team to influence Snowflake’s AI and ML product roadmaps based on field team and customer feedback.
• Partner with Product Marketing teams to spread awareness and support pipeline building via customer roundtables, conferences, events, blogs, webinars, and whitepapers

ON DAY ONE, WE WILL EXPECT YOU TO HAVE:

• 5+ years of experience building and deploying machine learning solutions in the cloud, including expert level experience with Python and popular third party packages (Pandas, Numpy, Tensorflow, sklearn, Pytorch, etc.)
• 1-2 years of experience working with LLMs on real-world use cases, including exposure to developer tools like langchain.
• Applied knowledge of techniques needed to build performant Generative AI solutions with LLMs and foundation models in enterprise settings, like few shot prompt engineering, RAG, search and retrieval techniques, etc. 
• 2+ years of working with cloud native ML and AI tools such as Sagemaker, AzureML, or VertexAI.
• Strong knowledge of SQL
• Strong knowledge of data engineering technologies and tools (dbt, Airflow, etc)
• Outstanding presentation skills to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
• Bachelor’s Degree in computer science, engineering, mathematics or related fields, or equivalent experience

BONUS POINTS FOR EXPERIENCE WITH THE FOLLOWING:

• 2+ years experience building and deploying ML or data engineering applications and solutions on Spark
• Working knowledge of R, Scala, or other scripting languages
• 1+ years of practical Snowflake experience.
• Experience working in a go-to-market team at a SaaS company or technical consulting organization.
• Knowledge of and experience with large-scale database technology (e.g. Snowflake, Netezza, Exadata, Teradata, Greenplum, etc.)
• Masters Degree in computer science, engineering, mathematics or related fields, or equivalent experience.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. 

How do you want to make your impact?

Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.

The application window is expected to be open until September 22, 2024. This opportunity will remain posted based on business needs, which may be before or after the specified date.

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Last updated on Aug 23, 2024