Nearby AI Internship Program - Engineering Track
$0k - $0k • Mountain View, California, United States • Internship
Posted 1mo ago
Job Location
Mountain View, California, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Internship
Categories
AI Engineer
About the job
Nearby AI, a NewsBreak company, is building a trust-first marketplace for local home services. We aim to provide homeowners with clarity and control regarding service needs and costs, while helping service providers win work based on fit and outcomes. As a small founding team, we operate with a commitment to evidence-based decision-making and core product principles that prioritize user trust and fair practices. We are seeking individuals who are curious, take ownership, and are eager to make an impact.
Responsibilities
- Build the personalized provider-recommendation pipeline end-to-end.
- Use LLMs to extract service requirements, preferences, and constraints from user inputs.
- Combine semantic search, recommendation algorithms, and provider features for improved relevance.
- Develop backstage pipelines for intent understanding, retrieval, provider comparison, and recommendation decisions.
- Integrate multi-source data including business information, reviews, credentials, and service coverage.
- Build evaluation datasets, analyze failure cases, and improve quality, reliability, and latency.
- Ship and iterate on the recommendation system.
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.
- Experience with embeddings, hybrid search, reranking, learning to rank, or personalized matching (preferred).
- Experience with Elasticsearch, MongoDB, PostgreSQL, vector databases, or data pipelines (preferred).
- Shipped products, open-source contributions, or independent projects showing individual impact (preferred).
Benefits
- Discretionary bonus
- Stock options