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TikTok

Short-form video platform with ads

Technical Lead Machine Learning Engineer - Agent & Multi-Agent Systems, AIGC Risk Intelligence

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeSeattle, WA, USAIn-person

About the Job

Requirements

  • At least 5 years of experience in software engineering or applied AI systems.
  • Deep understanding of LLM-based agent architectures, including ReAct-style reasoning, tool-calling systems, workflow orchestration, and memory design patterns.
  • Experience designing distributed or modular AI systems.
  • Strong backend engineering skills in Python or an equivalent language.
  • Experience operating systems in adversarial or high-stakes environments.

Responsibilities

  • Design structured agent workflows, such as Evaluate → Validate → Reflect → Summarize.
  • Implement ReAct-style tool allocation and reasoning frameworks.
  • Develop short-term and long-term memory architectures.
  • Ensure agent systems remain robust under adversarial and evolving conditions.
  • Design orchestration layers that coordinate vertical domain agents.
  • Build modular skill systems for extensibility and reuse.
  • Define execution graph standards and planning abstractions.
  • Establish traceability mechanisms for debugging and auditability.
  • Architect systems that can identify previously unseen risk patterns.
  • Implement execution trace-driven optimization loops.
  • Translate feedback signals, including false positives/false negatives, reviewer overrides, and drift signals, into system improvements.
  • Enable proactive rather than purely reactive detection systems.
  • Define traceability, observability, and guardrail requirements for agent systems.
  • Evaluate and integrate multi-agent frameworks where appropriate.
  • Ensure production readiness, scalability, and reliability.
  • Own the technical roadmap for agent and multi-agent systems.
  • Partner cross-functionally with Risk, Safety, Infrastructure, and Machine Learning teams.
  • Mentor engineers and drive architectural rigor.

Desired Qualifications

  • Experience in trust and safety, risk detection, or adversarial machine learning.
  • Familiarity with multi-agent orchestration frameworks.
  • Experience building systems with execution trace logging and observability.
  • Background in reinforcement-learning-style policy optimization or iterative system refinement.
  • Demonstrated experience leading high-impact technical initiatives.

About the Company

TikTok

Short-form video platform with ads

TikTok is a short-form mobile video platform that lets people create, discover, and share quick videos. Users upload vertical clips, edit them with built-in tools, and browse a personalized feed powered by an algorithm that highlights relevant content. Advertisers can use in-feed ads, branded hashtags, and the Business Center to plan and measure campaigns, making it easy for brands to reach a global audience. Its goal is to inspire creativity and bring joy by helping people express themselves and by connecting brands with a wide audience.

Company size
10,001+
Company stage
Grant
Total funding
$740K
Headquarters
Santa Monica, CA
Founded
2016

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