Intern - RAG Applications

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In addition to our core athlete management system, Apollo is developing a new generation of AI-driven products designed to help coaches, practitioners, and athletes interact with performance content through natural language. These systems combine large language models, semantic search, and structured performance data to deliver exercises, training content, and insights directly to users through mobile and web interfaces.

Apollo is seeking a highly motivated AI & Software Engineering Intern to support the development of our emerging AI-powered data query systems. These systems allow users to interact with large sports performance datasets through natural language and voice interfaces, enabling practitioners to ask questions like: "Who had the highest countermovement jump height last season?" "What was the team’s average eccentric peak power by body mass last year?" and receive structured answers generated directly from underlying databases.

The internship will focus on improving the underlying LLM-powered data query infrastructure, including natural language query interpretation, schema understanding, SQL generation, and response validation systems. This role blends elements of AI engineering, retrieval-augmented generation (RAG), backend systems, and data infrastructure. Interns will work directly with Apollo’s engineering and product teams to improve how LLM-powered systems translate user queries into database queries and deliver reliable analytical responses.

This position is ideal for students interested in LLM systems, data infrastructure, and building production AI tools that interface directly with real-world databases.

Responsibilities

  • • Support the development and improvement of Apollo’s LLM-powered natural language query systems that allow users to interact with structured sports performance datasets through conversational interfaces
    • Work with engineering and product teams to improve query interpretation, schema grounding, and SQL generation pipelines that translate user questions into reliable database queries
    • Build and maintain evaluation frameworks to measure the performance, accuracy, and reliability of AI query systems
    • Develop internal tooling to test and compare LLM prompts, embeddings, retrieval pipelines, and model configurations
    • Create and maintain evaluation datasets and benchmarking pipelines used to measure text-to-SQL and database query accuracy
    • Build tools to evaluate correctness, latency, and reliability of generated queries and AI responses
    • Improve response formatting, validation, and guardrails to ensure AI-generated answers are accurate and interpretable
    • Assist in integrating AI-driven services into Apollo’s web and mobile applications
    • Contribute to internal tooling and infrastructure used for AI experimentation, testing, and deployment
    • Work with a modern AI appliction stack: Python, TypeScript, React, SQL, LLM APIs, Retrieval Augmented Generation (RAG) systems, and Git / CI/CD workflows

    Requirements

    • Currently pursuing or recently completed a master’s degree in computer science, data science, Statistics, Finance, Sports Analytics, or a related field.
    • Able to work 40 hours per week, including 5 days in-office.
    • Strong programming experience in Python, TypeScript, or a similar language
    • Strong familiarity with SQL and relational databases Interest in AI systems, LLMs, or applied machine learning
    • Comfortable working with APIs, backend systems, and data pipelines
    • Experience building web applications, APIs, or backend services
    • Experience with CI/CD pipelines, Git workflows, or deployment infrastructure

      This internship offers hands-on experience working with real-world datasets used by elite professional and collegiate sports organizations. Interns will gain exposure to modern data and AI infrastructure, including machine learning workflows, model deployment, MLOps practices, and backend systems that support large-scale analytics platforms.

      This is an opportunity for early career technical individuals to gain experience building real-world AI products used by professional sports organizations with strong potential for future full-time opportunities based on performance.

      Please submit your resume and a cover letter to info@apollov2.com.

      ApolloV2 is an equal opportunity employer with a commitment to hiring people with diverse backgrounds. We do not discriminate based on age, civil or family status, disability, ethnicity, gender, race, religion, or sexual orientation.