Senior ML Architect, Applied Field Engineering

Senior ML Architect, Applied Field Engineering – Overview

Join Snowflake as a Senior ML Architect in Applied Field Engineering. In this role, you will provide strategic and technical advisory while designing and architecting AI/ML solutions on the Snowflake AI Data Cloud. You will collaborate with cross‑functional teams 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.
• Build compelling AI ML demos and proof of concept (POCs) for customers.
• 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, and technical collateral such as notebooks and demos.
• Influence, tailor and maintain Sales Engineering AI and ML selling assets, including customer presentations, demonstrations, and customer stories.

• 5+ years of experience building and deploying machine learning and generative AI solutions in the cloud.
• MLOps experience on a major ML platform (e.g., Databricks, Sage Maker): built shared pipelines/templates for teams and deployed/operated production models with monitoring and alerts; wrote unit/integration tests and used Git/CI.
• Hands‑on scripting experience with Python, with experience using libraries such as Pandas, Hugging Face, XGBoost, PyTorch, Tensor Flow, Sci Kit‑Learn or similar.
• Have the following AI and ML Engineering skills:
  • Data Cleansing
  • Work with large datasets, and perform data quality evaluation/checks
  • Feature engineering
  • Determine relevant features for training and evaluation
  • Optimization of model performance/accuracy
  • MLOps and lifecycle management
• Strong skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations 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 Lang Chain, Llama Index, and NeMo‑Guard.
• Experience and understanding of large‑scale infrastructure‑as‑a‑service platforms (e.g., AWS, Microsoft Azure, GCP, etc.).
• 1+ years of practical Snowflake experience.

This role is eligible to participate in Snowflake’s commission plan and it is common for employees in this role to receive total on‑target earnings of $237,700 – $330,750. The estimated base salary for this role is $178,275 – $248,062. Additionally, this role is eligible to participate in Snowflake’s equity plan. This role is also eligible for a competitive benefits package that includes medical, dental, vision, life, and disability insurance;

401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.

The application window is expected to be open until November 3, 2025. This opportunity will remain posted based on business needs, which may be before or after the specified date.

Snowflake is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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.