Applied AI Intern
Paid Applied AI internship focused on building, evaluating, and deploying production-oriented AI applications, including agents, RAG pipelines, and LLM integrations. Requires strong Python skills and current or recent study in a relevant technical field.
About the job
Responsibilities
- Build and iterate on AI pipelines, agents, and data applications for customer or product engagements.
- Translate business goals into engineering tasks, prototypes, and measurable outcomes.
- Contribute to evaluation frameworks, test datasets, observability, and experiments that improve AI quality.
- Productionize solutions with reliability, safety guardrails, monitoring, and human-review workflows.
- Collaborate with data science and engineering teams while writing clean, tested Python and SQL.
- Participate in design reviews, code reviews, debugging, documentation, and software development activities.
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 machine learning, LLMs, generative AI, RAG, AI agents, or data-intensive applications.
- Strong Python programming skills.
- 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-haves
- Project involving LLMs, RAG, agents, machine learning, or data systems.
- Experience with Snowflake, Snowpark, Cortex, Streamlit, Spark, AWS, Azure, or Google Cloud.
- Understanding of distributed systems, model serving, or inference infrastructure.
- Experience creating evaluation datasets, test suites, benchmarks, or AI observability.
- Previous internship, research, open-source, or personal software engineering experience.
Compensation and Benefits
- Paid, full-time internship.
- Mentorship, regular feedback, and support from experienced AI engineers and researchers.
- Hands-on experience with Snowflake Cortex, Snowpark, Python, SQL, and modern AI development tools.
- Exposure to the engineering lifecycle, including design, implementation, evaluation, testing, deployment, and monitoring.
- Internship duration of at least 4 months; 6 months recommended, with up to 12 months supported.
Skills
Python, SQL, Machine Learning, LLMs, Generative AI, Retrieval-Augmented Generation, AI Agents, Snowflake, Snowpark, Streamlit, Spark, AWS, Azure, GCP, Distributed Systems
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