Pocket FM Software Engineer Intern

About Company

Pocket FM, founded in 2018, is India’s leading audio storytelling platform, transforming the way millions consume stories. Offering high-quality serialized content across genres such as Romance, Drama, Thriller, Fantasy, Sci-Fi, and Mythology in eight languages, Pocket FM has built a strong global presence with over 200 million listeners worldwide. With users spending an average of 120 minutes daily on the platform, it has emerged as one of the fastest-growing audio platforms, rapidly expanding its reach across the US, Europe, LATAM, and Southeast Asia.

Role Overview

We’re looking for a Backend Engineering Intern to join our AI/ML platform team. In this role, you’ll work closely with experienced engineers to build and support backend services that power AI-driven features. This internship is designed for candidates who are eager to learn backend engineering, distributed systems, and AI infrastructure in a real-world environment.

Responsibilities

• Assist in developing and maintaining backend services, APIs, and microservices using Python or Go.
• Support the implementation of retrieval systems and RAG pipelines, including working with vector databases.
• Help build and optimize backend components that support AI-powered features at scale.
• Contribute to improving performance, reliability, and security of backend services.
• Integrate backend services with cloud infrastructure, databases, caching, and storage systems.
• Collaborate with AI/ML engineers to integrate LLM APIs and support inference workflows.
• Write clean, maintainable, and well-tested code following engineering best practices.
• Participate in code reviews, documentation, and CI/CD workflows under mentorship.

Required Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• Experience with Python or Go through coursework, projects, or internships.
• Basic understanding of backend concepts such as APIs, databases, and microservices.
• Familiarity with backend frameworks like FastAPI, Flask, Gin, or Echo is a plus.
• Understanding of RESTful APIs; exposure to gRPC or GraphQL is helpful but not required.
• Experience with databases such as Postgres, MongoDB, or Redis through academic or personal projects.
• Interest in AI systems, LLMs, and backend infrastructure.
• Strong problem-solving skills and eagerness to learn in a fast-paced environment.

Skills To Have

• Exposure to vector databases (Pinecone, FAISS, Weaviate) or information retrieval concepts.
• Familiarity with LLM APIs (OpenAI, Anthropic, etc.) through side projects or coursework.
• Experience using Docker or basic containerization concepts.
• Awareness of cloud platforms (AWS, GCP, or Azure) from labs or projects.
• Knowledge of CI/CD pipelines, monitoring, or observability tools (Prometheus, Grafana, Datadog).
• Interest in AI orchestration frameworks such as LangChain or LlamaIndex.