Snowflake

Snowflake delivers the AI Data Cloud to help organizations share data, build apps and power their business with AI.

Senior AI/ML Architect, Applied Field Engineering

Field EngineerField EngineerFull TimeRemoteTeam 5,001-10,000Since 2012H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

13 days ago

Salary

Not specified

No structured requirement data.

Job Description

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more.

Role Description

Our Solution Engineering organization is seeking an AI Specialist who can provide hands-on expertise and support while working with technical decision makers and data scientists to design and architect AI solutions built on the Snowflake AI Data Cloud.

This is a strategic role that works closely with cross-functional teams, including product, engineering, and the broader field organization to ensure successful execution and customer adoption of Snowflake’s AI & ML solutions.

  • Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the Americas.
  • Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases.
  • Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback.
  • Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos.
  • Influence, tailor and maintain Sales Engineering AI and ML selling assets, including customer presentations, demonstrations, and customer stories.

Qualifications

  • 5+ years of experience building and deploying machine learning and generative AI solutions in the cloud.
  • Familiarity and associated knowledge of generative AI techniques like RAG, few shot learning, prompt engineering, or fine-tuning that are used to operationalize enterprise AI use cases like interactive chat applications or text processing.
  • Deep knowledge of Python and common ML packages (such as LangChain, pandas, sklearn, and PyTorch) as well as data engineering tools and technologies like dbt, Airflow, and Spark.
  • Strong presentation skills to both technical and executive audiences, whether whiteboarding sessions or formal readouts and demos.
  • Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent experience preferred.

Requirements

  • Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
  • Experience and understanding of large-scale infrastructure-as-a-service platforms (e.g. AWS, Microsoft Azure, GCP, etc.)
  • 1+ years of practical Snowflake experience.
  • Knowledge of and experience with large-scale database technology (e.g. Snowflake, Netezza, Exadata, Teradata, Greenplum, etc.)

Benefits

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

Job Requirements

  • 5+ years of experience building and deploying machine learning and generative AI solutions in the cloud.
  • Familiarity and associated knowledge of generative AI techniques like RAG, few shot learning, prompt engineering, or fine-tuning that are used to operationalize enterprise AI use cases like interactive chat applications or text processing.
  • Deep knowledge of Python and common ML packages (such as LangChain, pandas, sklearn, and PyTorch) as well as data engineering tools and technologies like dbt, Airflow, and Spark.
  • Strong presentation skills to both technical and executive audiences, whether whiteboarding sessions or formal readouts and demos.
  • Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent experience preferred.
  • Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
  • Experience and understanding of large-scale infrastructure-as-a-service platforms (e.g. AWS, Microsoft Azure, GCP, etc.)
  • 1+ years of practical Snowflake experience.
  • Knowledge of and experience with large-scale database technology (e.g. Snowflake, Netezza, Exadata, Teradata, Greenplum, etc.)

Benefits

  • 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

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