Requirements

Currently pursuing or recently completed (within the last 12 months) a Bachelor's, Master's, or PhD in Computer Science, Engineering, Mathematics, Statistics, or a related field
Interest in ML, LLMs, generative AI, RAG, AI agents, or data-intensive applications
Strong programming skills in Python
Familiarity with version control, testing, debugging, and code reviews
Ability to work independently on well-scoped tasks, collaborate effectively, and communicate technical ideas clearly

Nice to Have

A project involving LLMs, RAG, agents, machine learning, or data systems
Experience with Snowflake, Snowpark, Cortex, Streamlit, Spark, or AWS, Azure, or GCP
Understanding of distributed systems, model serving, or inference infrastructure
Experience creating evaluation datasets, test suites, benchmarks, or observability for AI systems
Previous internship, research, open-source, or personal software engineering experience

Build and iterate on AI pipelines, agents, and data applications within team-led customer or product engagements
Turn business goals into engineering tasks, prototypes, and measurable outcomes with guidance from senior engineers
Contribute to evaluation frameworks, test datasets, observability, and experiments that improve AI quality
Help productionize solutions through reliability, safety guardrails, monitoring, and human-review workflows
Collaborate with customer data science and engineering teams while writing clean, tested Python and SQL
Participate in design reviews, code reviews, debugging, documentation, and other software development activities

Paid, full-time internship on the Applied AI engineering team
Mentorship, regular feedback, and support from experienced AI engineers and researchers
Hands-on work with Snowflake Cortex, Snowpark, Python, SQL, and modern AI development tools
Exposure to the engineering lifecycle, including design, implementation, evaluation, testing, deployment, and monitoring
Opportunities to present your work, collaborate with Product and Engineering, and be considered for future full-time or internship roles