Zendesk
Zendesk
Zendesk ұйымдарға әңгімелерді, қолдау сұрауларын және клиенттермен қарым-қатынастарды біртұтас ортада басқаруға көмектесетін клиенттерге қызмет көрсету және сату бағдарламалық жасақтамасын әзірлейді. Оның платформасы хабар алмасуды, тікелей чаттарды, жасанды интеллектке негізделген автоматтандыруды, деректердің құпиялылығы мен қорғалуына арналған құралдарды және агенттердің жұмыс кеңістігін біріктіреді. Бұл командаларға қызмет көрсету операцияларын ауқымы өскен сайын икемді түрде ұйымдастыруға мүмкіндік береді. Zendesk сонымен қатар кәсіби қызметтер мен оқыту ресурстарын ұсынады және жекелендірілген клиент өзара әрекеттестігіне, ықпалдастырылған жұмыс процестеріне, әртүрлілік пен инклюзияға және тұрақты дамуға басымдық беретінін мәлімдейді.

Senior Machine Learning Engineer, AI Agents

Advance AI agent planning, memory, evaluation, and safety for Zendesk’s customer service resolution platform. Build reinforcement learning systems using production trajectories.

Сипаттама

  • Design memory structures and autonomous learning methods for AI agents.
  • Improve agent architecture through ambiguous goal decomposition, memory tier management, selective skill acquisition, and A2A-based multi-agent delegation.
  • Build customer service agent models with reinforcement learning on production trajectories.
  • Lead reinforcement learning infrastructure, including reward curricula, rollout systems, and feedback loops.
  • Develop multi-turn evaluations and automated trajectory analysis.
  • Add CI quality gates and regression detection to prevent deployments when agent performance declines.
  • Implement enterprise guardrails with supervisor patterns, capability-based access controls, and output validation.
  • Collaborate with colleagues in Zendesk’s hybrid work environment.

Талаптар

  • At least five years of experience building production machine learning or AI systems.
  • Practical experience with agent architectures, including planning, tool dispatch, memory, and error recovery.
  • Strong evaluation judgment and experience creating internal evaluations.
  • Fluency in Python and PyTorch.
  • Familiarity with at least one agent framework.
  • Sound judgment about when to build custom solutions.
  • Reinforcement learning experience or substantial expertise with language models is optional; relevant areas include reward shaping, online and offline tradeoffs, and using reward hacking as a diagnostic signal.

Артықшылықтар

  • Hybrid work with the flexibility to work remotely for part of the week.
  • An inclusive workplace.
  • Reasonable accommodations for applicants with disabilities and disabled veterans.

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