Applied AI Intern — Build Production-Ready AI Pipelines

Snowflake; United States; On-site; USD 9,300 - 15,000; Full time

Benefits offered by this job

Mentorship

Hands-on with Snowflake Cortex

Career opportunities

Job summary

Snowflake is seeking an Applied AI Intern to join our engineering team in Warsaw, helping build, evaluate, and deploy AI applications for real customer use cases. You will work with experienced AI engineers on production-oriented systems, learning how to take a solution from prototype to production and contributing to reusable engineering assets and platform improvements.

You will gain hands-on experience with Snowflake Cortex, Snowpark, Python, SQL, and modern AI development tools, while

Qualifications

• Pursuing or recently completed degree in CS, Engineering, Math, or related field.
• Interest in ML, LLMs, RAG, or data-intensive AI.
• Strong Python programming.
• Ability to work independently and communicate clearly.

Responsibilities

• Build and iterate AI pipelines, agents, and data apps with the team.
• Translate business goals into engineering tasks with guidance.
• Contribute to evaluation, tests, observability, and AI quality.
• Help productionize solutions with reliability and safety guardrails.
• Collaborate with customer data teams; write clean Python/SQL.
• Participate in design and code reviews and documentation.

Skills

Python

ML basics

RAG/LLMs

English comms

Education

Bachelor's/Master's in CS/Engineering/Math

Tools

Snowflake Cortex

Snowpark

Spark

AWS/Azure/GCP

Job description

Snowflake is seeking an Applied AI Intern to join our engineering team in Warsaw, helping build, evaluate, and deploy AI applications for real customer use cases. You will work with experienced AI engineers on production-oriented systems, learning how to take a solution from prototype to production and contributing to reusable engineering assets and platform improvements.

You will gain hands-on experience with Snowflake Cortex, Snowpark, Python, SQL, and modern AI development tools, while