Machine Learning Intern

Role: Machine Learning Intern

Location: Bengaluru, India

Type: Internship

Internship Duration: 6 Months (Paid Internship)

Endee is a high performance vector database built for modern AI workloads such as semantic search, retrieval augmented generation, recommendation systems, and large scale vector search.

We focus on building AI infrastructure that delivers high recall, low latency, strong security, and cost efficiency. Endee is designed for teams building real world AI systems at scale.

This internship offers deep exposure to production grade AI infrastructure and vector database technologies used by AI driven companies.

We are looking for Machine Learning Engineer Interns who are excited about AI infrastructure, vector databases, and applied machine learning systems.

As an intern, you will work closely with experienced engineers and gain hands on experience designing, optimizing, and evaluating AI powered applications built on vector search and retrieval systems.

• Work on machine learning workflows involving embeddings, similarity search, and vector retrieval
• Assist in designing and optimizing semantic search and retrieval augmented generation pipelines
• Analyze performance, accuracy, and scalability of vector based systems
• Work with both structured and unstructured data for AI applications
• Support integration of vector databases into AI services and applications
• Write clean, well documented, and maintainable code
• Collaborate with engineering and research teams on AI system design

• Strong fundamentals in machine learning concepts
• Proficiency in Python
• Understanding of embeddings, similarity search, or NLP concepts
• Familiarity with Git and version control
• Ability to learn and work with new AI tools and systems

• Experience with large language models and RAG pipelines
• Familiarity with Docker or cloud environments
• Understanding of databases or search systems
• Prior open source contributions or research project experience

This internship follows a project based evaluation approach.

Candidates will be evaluated primarily based on a project created using the Endee vector database.

• Develop a well defined AI or ML project using Endee as the vector database
• Demonstrate a practical use case such as semantic search, RAG, recommendations, or similar AI workflows
• Host the project on GitHub
• Provide a clean and comprehensive README including:
• Project overview and problem statement
• System design or technical approach
• Explanation of how Endee is used
• Clear setup and execution instructions

• Share the GitHub repository link as part of the application or evaluation process

• Hands on experience with production grade AI infrastructure
• Practical exposure to vector databases and large scale retrieval systems
• Opportunity to contribute to an open source AI project
• Mentorship from experienced ML and systems engineers
• A strong portfolio project demonstrating real world AI skills