*Hybrid in Tampa, FL*
About Symple Lending
Symple Lending is a fast-growing fintech company focused on helping consumers regain control of their financial future. We combine innovative technology, data-driven strategies, and a high-performance team to deliver meaningful results for both our customers and partners.
The Role
We’re looking for a Generative AI Engineer Intern to join our Data & AI team in a hands-on, high-impact internship role working directly on real production AI systems. This is an unpaid internship opportunity designed for students or recent graduates who want practical experience building and improving enterprise-grade AI applications in a live financial services environment.
In this role, you’ll work alongside our Data Scientist to support and enhance Syble, Symple Lending’s AI-powered compliance platform that processes over 1,000 customer call transcripts per day. You’ll gain direct exposure to LLM engineering, prompt optimization, RAG pipelines, AWS infrastructure, and production AI workflows while contributing to systems used by sales leadership and executive teams.
If you enjoy building with AI, experimenting with new technologies, and solving real-world problems with data and automation, this role is for you.
What You’ll Do:
AI & LLM Engineering
- Write, test, and optimize prompts for our AI-powered compliance grading systems
- Build evaluation datasets and testing frameworks to measure model performance
- Assist in improving Retrieval-Augmented Generation (RAG) pipelines using ChromaDB and Amazon S3
- Experiment with chunking strategies, embedding models, and retrieval tuning
- Research and prototype new LLM frameworks, embeddings, and agentic AI workflows
Data & Analytics
- Write SQL queries against Amazon Redshift to analyze transcript and operational data
- Validate model outputs and support analytical workflows across sales and loan origination operations
- Use Python and Jupyter notebooks to explore data and build internal tooling
Pipeline Testing & Operations
- Support testing and QA for existing AI pipelines and production grading systems
- Identify edge cases, inconsistencies, and opportunities for system improvements
- Document prompt versions, pipeline logic, and model configurations to support scalability and maintainability
Why This Internship Stands Out
- Work directly on a live AI system processing 1,000+ real customer interactions daily
- Gain hands-on experience with LLMs, RAG pipelines, vector databases, and AWS-native AI systems
- Learn from an experienced Data Scientist with production AI and NLP expertise
- Exposure to AI development in a regulated financial services environment
- Build meaningful production experience that stands out on a resume
- Opportunity for future full-time employment based on performance
What We’re Looking For:
Required Qualifications
- Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or a related field
- Strong Python programming skills
- Basic understanding of LLM concepts, prompts, RAG, and hallucination challenges
- Familiarity with SQL and data querying
- Curious, self-motivated, and eager to learn in a fast-paced environment
Preferred Qualifications
- Experience with LangChain, LlamaIndex, or similar LLM orchestration frameworks
- Exposure to vector databases such as ChromaDB, Pinecone, or FAISS
- Familiarity with AWS services including S3, Lambda, or EC2
- Experience working with OpenAI, Anthropic, or similar LLM APIs
- GitHub portfolio or personal AI/ML projects
Nice to Have
- Experience with Jupyter notebooks and data exploration workflows
- Exposure to NLP concepts, including embeddings and semantic similarity
- Familiarity with pandas, NumPy, or machine learning workflows
- Coursework or self-study in machine learning or deep learning
Compensation
This is an unpaid internship intended to provide hands-on experience in production AI systems, mentorship, and career development opportunities. High-performing interns may be considered for future full-time opportunities at Symple Lending.
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