Applied AI Engineer, Advertising Agents (New Grad)

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 the Role

Are you a recent graduate excited to apply LLMs and Agent technology to real advertising products from day one? Join our advertising team to help build an AI-driven intelligent account hosting and optimization platform. You'll work alongside senior engineers to develop AI advertising expert systems (AI Agents) that diagnose accounts and safely auto-tune delivery in a closed optimization loop.

Your work will directly lower the delivery barrier for global advertisers on our platform. While ensuring the health and compliance of the account ecosystem, your contributions will help maximize advertisers' willingness to spend and platform revenue.

Responsibilities

• Contribute to the In-house AI Account Manager System: Support the design and implementation of components of the "AI Account Manager," including automated hosting, optimization scheduling, and monitoring across concurrently running advertiser accounts.
• Help Build Intelligent Diagnosis and Strategy Recommendation Models: Work with performance data and delivery history to help identify account health signals and delivery pain points (such as inability to scale volume, sudden drops in ROI, or budget capping); assist in using LLMs to generate actionable, auditable account-level tuning strategies.
• Support Reliability and Measurable Quality: Help build and maintain observability, dry-run safeguards, and offline/online evaluation pipelines that keep optimization quality measurable and catch regressions before they reach live spend.
• Collaborate and Learn: Work closely with senior engineers, the platform-side ad delivery algorithm team, and product managers, gaining exposure to how AI account management capabilities translate into commercial impact.

Minimum Qualifications

• Education Background: Bachelor's/Master's degree (recently completed or completing within the next 6 months) in Computer Science, Artificial Intelligence, Data Science, or related fields.
• Work Experience: No professional work experience required; relevant internships, research, coursework, or personal projects involving LLMs, agents, or ML are a plus. Exposure to building or experimenting with agentic systems (e.g., through coursework, hackathons, internships, or personal projects). Solid software-engineering fundamentals: ability to write clean, testable code; familiarity with asynchronous/concurrent programming and typed/data-modeled code.
• Core Technical Stack: Foundational understanding of LLMs, RAG, tool-use, and agent orchestration concepts (including MCP-style tool ecosystems), gained through coursework, projects, or self-study. Some hands-on experience with structured/schema-validated LLM outputs and modern model APIs (e.g., through class projects or internships). Familiarity with REST/API integration; exposure to deployment tools such as Docker or Kubernetes is a plus. Solid grounding in machine learning and AI fundamentals. Strong analytical skills and eagerness to learn complex problem-solving in a production environment.

Preferred Qualifications

• Internship or research experience involving large language models, agent-based systems, or recommendation/ads systems.
• Exposure to advertising or recommendation system concepts and metrics (CPA, ROAS, CVR, CTR, conversions).
• Personal or academic projects demonstrating initiative in building AI agents or automation tools.

What We Offer

A Launchpad for Applied AI Careers: Learn to apply cutting-edge Generative AI and Agent technologies to reshape the B-end ad monetization ecosystem, with mentorship from senior engineers.

Direct Commercial Impact: See your contributions reflected in real advertiser growth and the platform's revenue flywheel.

Top-tier Computing Resources and Environment: Access to industry-leading foundation models, large-scale computing infrastructure, and the opportunity to learn alongside world-class advertising, AI, and infrastructure engineers.