Solutions Architect AI/ML

Job Summary

Where Data Does More. Join the Snowflake team.

We are looking for individuals with expertise in data science and cloud architecture to develop exciting new services and features for our customers! The AI/ML Workloads Services team within the Professional Services Group is expected to collaborate with customers using Snowflake to expand their data cloud utilization, leveraging Snowflake's capabilities and extensive partner ecosystem to take data science pipelines from ideation to deployment and beyond. This is a highly technical, hands-on role that involves designing solutions based on requirements and coordinating with customer teams and, where necessary, system integrators.

As an AI/ML Solutions Architect at Snowflake, you will:

• Be the technical expert on all aspects of Snowflake related to AI/ML workloads.
• Build, deploy, and implement ML pipelines using Snowflake capabilities and/or partner tools in the Snowflake ecosystem based on customer requirements.
• Work hands-on as needed to build POCs demonstrating implementation techniques and best practices for Snowflake technologies for GenAI and ML workloads using SQL, Python, and APIs.
• Follow best practices, including ensuring knowledge transfer.
• Maintain a deep understanding of competitive and complementary technologies and vendors in the AI/ML space and how to position Snowflake relative to them.
• Collaborate at a deep technical level with consultants from system integrators to ensure successful positioning and adoption of Snowflake in customer environments.
• Provide guidance to resolve customer-specific technical challenges.
• Support the upskilling of other members of the Professional Services team.
• Collaborate with Product Management, Engineering, and Marketing to drive continuous improvement of Snowflake products and marketing.
• Be flexible to travel up to 25% for on-site customer collaboration.

Ideal Candidate Profile

The ideal Solutions Architect (AI/ML) will possess:

• Over 10 years of experience working with customers in a pre-sales or post-sales technical role.
• Presentation skills for technical and executive audiences, with the ability to present impromptu on a whiteboard or using presentations and demos.
• Deep familiarity with the entire data science lifecycle, including feature engineering, model development, model deployment, and model management.
• A strong understanding of MLOps, combined with technologies and methodologies for model deployment and monitoring.
• Experience and understanding of at least one public cloud platform (AWS, Azure, or GCP).
• Experience using at least one data science tool (e.g., AWS Sagemaker, AzureML, Vertex, Dataiku, DataRobot, H2O, Jupyter Notebooks).
• Experience with Large Language Models, search, and agent frameworks.
• Hands-on experience with SQL and scripting in at least one of Python, R, Java, or Scala.
• Experience using Pandas, PyTorch, TensorFlow, SciKit-Learn, or similar libraries.
• A Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent experience.

Bonus Points For:

• Experience with Databricks/Apache Spark.
• Experience implementing data pipelines using ETL tools.
• Hands-on experience in data science roles.
• Proven track record in enterprise software.
• Vertical expertise in core verticals such as FSI, Retail, or Manufacturing.

About Snowflake

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?

For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

Location Type

Remote

Employment Type

FullTime