Applied AI Engineer, Advertising Agents

United States·Mountain Viewmid

OtherMachine Learning EngineerApplied Ai EngineerData

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Quick Summary

Key Responsibilities

Own the algorithm and system design for the core "AI Account Manager" — realizing automated hosting, autonomous optimization,

Requirements Summary

Bachelor's/Master's degree or higher in Computer Science, Artificial Intelligence, Data Science, or related fields.

Technical Tools

OtherMachine Learning EngineerApplied Ai EngineerData

About the Role

~1 min read

Build In-house AI Account Manager System: Own the algorithm and system design for the core "AI Account Manager" — realizing automated hosting, autonomous optimization, and intelligent scheduling of optimization across many advertiser accounts running concurrently.
Construct Intelligent Diagnosis and Strategy Recommendation Models: Analyze advertisers' performance data and delivery history to assess account health and automatically diagnose delivery pain points (such as inability to scale volume, sudden drops in ROI, or budget capping), then use LLMs to generate and safely execute actionable, auditable account-level tuning strategies.
Ensure Reliability and Measurable Quality: Build the long-running services, observability, dry-run safeguards, and offline/online evaluation that keep optimization quality measurable and catch regressions before they reach live spend.
Cross-team Collaboration to Drive Growth: Work closely with the platform-side ad delivery algorithm team and product managers to transform AI account management capabilities into the platform's core commercial competitiveness, improving advertiser retention rate and overall consumption.

Requirements

~1 min read

Education Background: Bachelor's/Master's degree or higher in Computer Science, Artificial Intelligence, Data Science, or related fields.
Work Experience:

Possess a basic understanding of fields such as ad delivery platforms or recommendation systems; fresh graduates are acceptable.
Familiar with building, deploying, and optimizing agentic systems in production environments.
Strong software-engineering fundamentals: production-quality code, asynchronous/concurrent programming, typed and data-modeled code, and a solid testing discipline.

Core Technical Stack:

Master LLMs, RAG, tool-use, memory handling, and agent orchestration (including MCP-style tool ecosystems).
Hands-on with harness engineering, structured/schema-validated LLM outputs, and integration with modern model APIs.
Experience with REST/API integration and building reliable long-running services; familiar with modern deployment tools such as Kubernetes.
Solid grounding in machine learning and AI fundamentals; familiar with advertising or recommendation system concepts.
Possess excellent analytical and complex problem-solving abilities.

Industry Background: Algorithm experience in the field of ad delivery, with more than 2 years applying large-model capabilities to systems such as automated delivery, automated hosting, autonomous tuning, or automatic scheduling.
AI Production Experience: Experience landing commercial AI agents (agent-based systems), large-model instruction tuning, or multimodal models.
Business Acumen: Understanding of digital advertising mechanics and core metrics (CPA, ROAS, CVR, CTR, conversions) and of online A/B experimentation.

What We Offer

~1 min read

✓Technical Hard Power Born for Monetization: Participate in using the most cutting-edge Generative AI and Agent technologies to reshape the B-end ad monetization ecosystem under internet scale.

✓Direct Commercial Impact: Your algorithm and engineering optimizations will directly reflect on the real growth of advertisers and the platform's revenue flywheel.

✓Top-tier Computing Resources and Environment: Access to industry-leading foundation models, large-scale computing infrastructure, and opportunities to work side-by-side with 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

Location & Eligibility

Where is the job

Mountain View, United States

On-site at the office

Who can apply

About this job

Pay per year: $135,000–$185,000 a year; 23% below the $208,788 median for Machine Learning Engineer jobs on Jobera (1,002 salaries).
Who can apply: United States
Posted: 144 days ago
Employer: has 68 open jobs on Jobera.