AI Developer Internship

Rebel Who

Why Rebel Why This Job. Some people like the status quo the safe and the mundane. Others challenge every convention in the book create new values and expectations and change their world. They are the Rebels. They are the Challengers. If this is you read on.

Rebel Athletic is a classic Challenger Brand. Established in 2013 by Ernst & Young Entrepreneur of the Year 2020 Karen Aldridge to challenge the lowly conventions of the AllStar Cheer apparel market. Rebel is now the undisputed AllStar Cheer market thought and style leader.

Over the past 10 years Rebel has turned heads quicker than any other manufacturer and expanded into School and Sideline Cheer Dance and everyday athletic wear all with a trademark sparkle. Rebels cuttingedge designs technological innovations and unstinting focus on service quality choice and value have set a new standard in an industry that was starving for something new. Rebel is the brand that everyone else follows. So if you want to be a follower go and work for them. If not become a Rebel.

Summary of Position:

We are seeking an enthusiastic AI Developer / Engineer Intern with a passion for RAG natural language processing (NLP) and machine learning. This internship offers a unique opportunity to explore and contribute to the rapidly growing field of generative AI working directly on projects that leverage both retrieval algorithms and large language models.

As an AI Developer / Engineer Intern focused on RetrievalAugmented Generation you will:

Collaborate with AI engineers and data scientists to design prototype and rene NLP and retrieval pipelines.

Work on integrating large language models (LLMs) with external knowledge sources databases document repositories APIsto enable contextdriven text generation.

Gain handson experience with modern NLP frameworks (e.g. Hugging Face Transformers spaCy) and retrieval technologies (e.g. ElasticSearch vector databases).

This position will immerse you in the endtoend development of RAG systemsfrom data

ingestion and indexing to model development and deployment.

Duties and Responsibilities:

Data Collection & Preprocessing

Gather and clean text and metadata from various sources.

Prepare data for indexing and retrieval ensuring highquality content for generative models.

Retrieval Pipeline Development

Experiment with vectorbased search BM25 and hybrid retrieval techniques.

Integrate external APIs and structured/unstructured data to enrich context for language models.

Model Experimentation & Tuning

Finetune large language models (LLMs) with retrievalaugmented data to improve accuracy and relevance.

Implement prompt engineering strategies to generate contextually accurate and coherent responses.

Performance Monitoring & Evaluation

Develop metrics to evaluate the effectiveness of both retrieval and generation components.

Conduct error analysis to identify bottlenecks and propose enhancements.

Collaboration & Documentation

Collaborate with crossfunctional teams (AI researchers software engineers product managers) to align project goals.

Maintain clear documentation on model architectures experiments and performance benchmarks.

Qualifications:

Basic Qualications

Currently pursuing or recently graduated with a degree in Computer Science Data Science or a related discipline.

Familiarity with machine learning and NLP concepts (e.g. embeddings tokenization transformers).

Prociency in Python and exposure to relevant libraries (e.g. Hugging Face Transformers PyTorch TensorFlow).

Understanding databases or search engine concepts such as SQL/NoSQL or ElasticSearch.

Strong analytical and problemsolving skills.

Preferred Qualications

Coursework or practical experience in information retrieval text mining or NLP.

Exposure to vector databases (e.g. Pinecone Weaviate Milvus) and knowledge of similarity search.

Experience with prompt engineering or netuning large language models.

Familiarity with cloud platforms (AWS Azure GCP) and containerization (Docker Kubernetes).

Knowledge of software development practices (Git Agile CI/CD).

What We Offer

HandsOn RAG Experience: Directly contribute to retrieval pipelines and LLM integrations for realworld applications.

CuttingEdge Environment: Work with stateoftheart NLP frameworks vector search engines and largescale language models.

Professional Growth: Participate in workshops conferences and seminars to expand your technical and professional network.

Potential for FullTime Hire: Outstanding interns may be considered for future fulltime roles.