Nearby AI Internship Program - Engineering Track

The role

Help build the personalized provider-recommendation pipeline end to end: user understanding with LLMs, provider retrieval and ranking, backstage agent workflows, multi-source knowledge integration, and evaluation, working with engineers and product managers from design through launch.

• User understanding and personalization: use LLMs to extract service requirements, preferences, and constraints from conversations, profiles, and context
• Provider retrieval and ranking: combine semantic search, recommendation algorithms, and provider features (capabilities, coverage, transaction-backed reputation, user fit) to improve relevance and coverage
• Agent workflows: build backstage pipelines connecting intent understanding, retrieval, provider comparison, and recommendation decisions, with explanations a user can check
• Multi-source data and knowledge integration: entity matching across business information, reviews, credentials, and service coverage
• Evaluation and delivery: build evaluation datasets, analyze failure cases and user feedback, improve quality, reliability, and latency; ship and iterate

Qualifications

Minimum

• 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; initiative to own results.

Preferred

• Embeddings, hybrid search, reranking, learning to rank, or personalized matching.
• 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.

Pay and benefits

The US base salary range for this full-time position is listed below. Pay may vary based on a number of factors including job-related skills, level, experience, geographic location and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talents. Depending on the position, the role may also be eligible for discretionary bonus and options. Your recruiter can share more details during the hiring process.

Annual Base Pay Range $30—$70 USD

Cpra

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