Senior AI/ML Observability & Data Systems Engineer – Remote

Snowflake; United States; Remote; USD 221,000 - 288,000; Full time

Job summary

Snowflake is seeking experienced Senior Software Engineers to design, develop, and maintain core AI/ML observability systems within a scalable data processing platform. You will implement techniques for monitoring ML and Generative AI models, while improving reliability and resource efficiency across services.

You will assume a technical leadership role in ML observability, data infrastructure, and model explainability, contributing to customer-facing AI products, and supporting a fast-moving,

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Electrical Engineering or related field.
• 5+ years of progressive post-baccalaureate experience in the role or related occupation.
• Experience designing and building database systems, compilers, and developer tools.
• Experience developing applications using Java.
• Experience with SQL and database technologies.
• Experience designing data warehouses and large-scale data processing solutions.
• Contributing to open-source projects is a plus.

Responsibilities

• Design, develop, and maintain core AI/ML observability components.
• Implement and optimize scalable data processing infrastructure and model monitoring.
• Lead design and implementation of ML observability, data infrastructure, and model explainability features.
• Collaborate on platform features for scalable ML and Generative AI use cases.
• Telecommuting permitted.

Skills

Java

SQL

ML observability

Big data

Education

Bachelor’s degree in Computer Science or related field

Tools

Hadoop

Job description

Snowflake is seeking experienced Senior Software Engineers to design, develop, and maintain core AI/ML observability systems within a scalable data processing platform. You will implement techniques for monitoring ML and Generative AI models, while improving reliability and resource efficiency across services.

You will assume a technical leadership role in ML observability, data infrastructure, and model explainability, contributing to customer-facing AI products, and supporting a fast-moving,