Senior AI/ML Architect, Applied Field Engineering

Snowflake3 months ago

Location

US-CA-Menlo Park

Type

Full Time

Salary

USD 165,000 – 216,562

Level

Senior

Role

ML Engineer

Posted

Nov 26, 2025

Full TimeSenior

The role

Summary

Snowflake is seeking a Senior AI/ML Architect to serve as the technical expert for Snowflake's AI and ML solutions, working directly with enterprise customers across the Americas. This strategic role combines hands-on technical expertise in machine learning and generative AI with customer-facing responsibilities, requiring 5+ years of experience in cloud-based ML solutions and deep knowledge of Python and ML frameworks.

What you'll do

Technical Expert Role: Position Snowflake's AI and ML features and value to technical stakeholders at enterprise customers across the Americas

POC Leadership: Partner with account teams and customer champions to scope and drive proof-of-concepts to success, including executive readouts and business value cases

Product Collaboration: Collaborate with Snowflake's product and engineering teams to influence AI and ML roadmaps based on customer feedback

Content Creation: Publish scaling content including blog posts, conference presentations, technical notebooks, and demos

Sales Asset Management: Influence, tailor, and maintain Sales Engineering AI and ML selling assets, including customer presentations, demonstrations, and customer stories

What we look for

Technical

Machine Learning Expertise5+ years of experience building and deploying machine learning and generative AI solutions in the cloud

Generative AI TechniquesFamiliarity with RAG, few-shot learning, prompt engineering, and fine-tuning for enterprise AI applications

Python ProgrammingDeep knowledge of Python and common ML packages including LangChain, pandas, sklearn, and PyTorch

Data Engineering ToolsExperience with data engineering technologies like dbt, Airflow, and Spark

Presentation SkillsStrong presentation abilities for both technical and executive audiences, including whiteboarding and formal demonstrations

Education

Bachelor's DegreeBachelor's degree required in any field

Master's Degree (Preferred)Master's degree in computer science, engineering, mathematics, or related fields preferred

Experience

Cloud ML ExperienceMinimum 5+ years building and deploying ML solutions in cloud environments

Enterprise AI ApplicationsExperience with interactive chat applications, text processing, and other enterprise AI use cases

Technical LeadershipExperience working with technical decision makers and data scientists in enterprise environments

Skills

Required skills

Python ProgrammingDeep expertise in Python with focus on ML libraries and data processing

Machine Learning FrameworksProficiency with PyTorch, scikit-learn, pandas, and other ML packages

Generative AI TechniquesKnowledge of RAG, prompt engineering, fine-tuning, and few-shot learning

Data EngineeringExperience with dbt, Airflow, Spark, and data pipeline technologies

Cloud PlatformsExperience deploying ML solutions on AWS, Azure, or Google Cloud Platform

Technical PresentationStrong ability to present to both technical and executive audiences

Nice to have

LLM Ecosystem ToolsWorking knowledge of LangChain, LlamaIndex, and other open-source LLM packages

Snowflake Platform1+ years of practical experience with Snowflake data cloud platform

Large-Scale DatabasesKnowledge of enterprise database technologies like Teradata, Netezza, or Greenplum

Infrastructure PlatformsUnderstanding of large-scale IaaS platforms and cloud architecture

Content CreationExperience with technical writing, blogging, and conference presentations

Compensation & benefits

Salary

USD 165,000 – 216,562 (annual)

Stock options

Available

Benefits

Comprehensive Health Coverage

Full medical, dental, and vision insurance coverage

Stock Options

Equity participation in Snowflake's growth through stock option programs

Professional Development

Conference attendance, training opportunities, and continuous learning support

Flexible Work Environment

Collaborative culture focused on impact, innovation, and career growth

Career Advancement

Opportunities to work with cutting-edge AI/ML technology and influence product roadmaps

Interview process

1
Initial Screening — Phone or video screen with recruiter to discuss background and role fit
2
Technical Interview — Deep technical discussion covering ML/AI expertise, Python skills, and hands-on experience
3
Customer Scenario Interview — Role-playing customer interactions and technical presentations
4
Leadership Interview — Discussion with hiring manager about strategic thinking and collaboration skills
5
Final Round — Onsite or virtual panel interview with cross-functional team members