Intern - LLM Applications

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 Intern to support the development of our emerging AI-powered chatbot products. These systems allow users to interact with large libraries of training and rehabilitation content through conversational interfaces, retrieving relevant exercises and videos based on user intent. The internship will focus on improving the underlying AI infrastructure, experimentation systems, and deployment workflows that power these products. This role blends elements of AI engineering, experimentation infrastructure, backend systems, and product development. Interns will work directly with Apollo’s engineering and product teams to improve how our LLM-powered systems interpret user queries, retrieve relevant content, and integrate with our mobile and web applications. This position is ideal for students interested in LLM systems, applied AI infrastructure, and building real production AI products.

Responsibilities

  • Support the development and improvement of Apollo’s LLM-powered retrieval systems used to deliver training and rehabilitation content through conversational interfaces.
  • Work with engineering and product teams to improve query interpretation, semantic search pipelines, and content retrieval systems.
  • Contribute to improving ranking, filtering, and metadata systems used to match user prompts with relevant exercise and training content.
  • Assist in integrating AI-driven services into Apollo’s mobile and web applications.
  • Build tooling to test different embeddings, prompts, and model configurations, and create and maintain evaluation datasets used to benchmark retrieval performance.
  • Assist in improving the deployment and infrastructure supporting Apollo’s AI systems, and assist in integrating AI-driven services into Apollo’s mobile and web applications.
  • Collaborate with engineering teams to improve scalability and operational reliability of AI services.
  • Contribute to building CI/CD workflows and automated testing pipelines, and assist in deploying AI services to cloud or edge environments used by Apollo applications.

Requirements

  • Currently pursuing or recently completed a master’s degree in data science, Statistics, Finance, Sports Analytics, or a related field.
  • Able to work 40 hours per week, including 5 days in-office.
  • Comfortable working in a fast-paced startup environment with evolving product priorities
  • Strong programming experience in Python, TypeScript, or a similar language
  • Familiarity with relational databases and SQL
  • Interest in AI systems, LLMs, or applied machine learning
  • Strong analytical reasoning and problem-solving ability
  • Comfortable working with data pipelines, APIs, and backend systems
  • Ability to communicate clearly with both technical and non-technical stakeholders
  • Ability to work independently while collaborating with engineers and product leadership

‍

Preferred Qualifications

  • Experience with LLM APIs, embeddings, or vector databases
  • Experience building web applications or APIs
  • Experience with CI/CD, Git workflows, or deployment infrastructure
  • Experience working with large datasets or experimentation frameworks
  • Interest in sports science, performance analytics, or biomechanics

‍

    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.