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Open nowPosted 55 days ago

Nearby AI Internship Program - Engineering Track

NewsBreak66 open roles

Pay
$30 – $70 an hour
Where
Mountain View, California, United States
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Your applicationOpen nowNearby AI Internship Program - Engineering TrackNewsBreak · Mountain View, California, United States

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on NewsBreak's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

13.4% of postings close within 7 days. Measured by our own scanner across the market. NewsBreak postings stay open a median of 51 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: posted 55 days ago

NewsBreak median: 51 days open

The posting

About NewsBreak

Local life runs on local information. What happened down the street? Who can fix this? Where should we go tonight? NewsBreak started in 2015 to answer these questions, and today more than 40 million people a month rely on us to follow what’s going on in their zip code.

Three platforms with one vision: powering local life. Led by founder and CEO Jeff Zheng, NewsBreak is our local life and news platform; Nearby AI connects people with local businesses; and NDot AI helps publishers and creators grow and earn.

Building for the long term. A $115 million Series C made us a unicorn in 2021, and we keep investing in our people. We’re Great Place to Work® certified and named to Fast Company’s Best Workplaces for Innovators (2025) and Fortune’s Best Workplaces in the Bay Area™ (2026).

Everyone makes an impact. Whether you write code, shape products, tell our story, or run the business, we want people who own projects end to end, stay curious, and speak up. Join us.

Learn more at: NewsBreak, Nearby AI, NDot AI

About Nearby AI

Nearby AI is a new company from NewsBreak building a trust-first marketplace for local home services. We help homeowners understand a problem, what it should reasonably cost, and whether to hire at all before they are connected to a provider, and we help service providers win work on fit and outcomes rather than on speed of contact.

Our mission: give people clarity and control from the first sign of a problem to a job done right, and give good contractors work they are equipped to win.

We are a small founding team. We work from evidence, keep a written record of decisions, and hold a short set of product principles we do not trade for revenue: no pay-for-rank, no sharing of customer contact information beyond what the customer approved, and no quality claims we cannot substantiate.

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.

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

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