Applied AI Engineer, Advertising Agents (New Grad)

What you'd do

• 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.

What they want

• 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.

What you get

• 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.
• Health, dental, and vision care for you and your family (100% coverage for employee)
• Top-tier 401(K) plan with company matching
• Paid time off and paid holidays
• FSA, HSA and commuter benefits programs
• Team activity budget