Nearby AI Internship Program - Engineering Track

NewsBreak•Mountain View, CA

1d•$30 - $70

About The Position

NewsBreak is a Content Intelligence platform that has reached unicorn status and is recognized by Fast Company. Nearby AI, a new company from NewsBreak, is building a trust-first marketplace for local home services. This role is part of the Nearby AI team, focused on building a personalized provider-recommendation pipeline end-to-end. This includes user understanding with LLMs, provider retrieval and ranking, backstage agent workflows, multi-source knowledge integration, and evaluation, working closely with engineers and product managers from design through launch.

Requirements

Pursuing a bachelor's degree or higher in Computer Science, AI, or a related field.
Proficient in Python or Java with solid data structures and algorithms.
Hands-on experience developing LLM applications or agents (RAG, agent workflows, evaluation harnesses).
Understanding of search, recommendation, or ML fundamentals.
Strong problem-solving and communication skills; initiative to own results.

Nice To Haves

Embeddings, hybrid search, reranking, learning to rank, or personalized matching.
Experience with Elasticsearch, MongoDB, PostgreSQL, vector databases, or data pipelines.
Shipped products, open-source contributions, or independent projects showing individual impact.
Research and personal projects count; GitHub links and demos welcome.

Responsibilities

Use LLMs to extract service requirements, preferences, and constraints from conversations, profiles, and context.
Combine semantic search, recommendation algorithms, and provider features (capabilities, coverage, transaction-backed reputation, user fit) to improve relevance and coverage.
Build backstage pipelines connecting intent understanding, retrieval, provider comparison, and recommendation decisions, with explanations a user can check.
Perform entity matching across business information, reviews, credentials, and service coverage.
Build evaluation datasets, analyze failure cases and user feedback, improve quality, reliability, and latency; ship and iterate.