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Zendesk
Zendesk
5001 – 10.000 Zaposleni
Sponzor vizuma H1BLogistikaSvetovanjeTrženje
Zendesk razvija programsko opremo za podporo strankam in prodajo, ki organizacijam pomaga upravljati pogovore, zahtevke za podporo in odnose s strankami v enem povezanem okolju. Njegova platforma združuje sporočanje, klepet v živo, avtomatizacijo, ki jo poganja umetna inteligenca, orodja za zasebnost in zaščito podatkov ter delovni prostor za agente, ekipam pa omogoča prilagodljive načine organiziranja podpornih dejavnosti med njihovo rastjo. Zendesk ponuja tudi strokovne storitve in izobraževalne vire, pri čemer poudarja personalizirane interakcije s strankami, integrirane delovne tokove, raznolikost in vključevanje ter trajnost.
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Delovna mesta v podjetju

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.

AUAvstralijaHibridnoPolni delovni časSeniorZahtevani Jezik: angleščinaInženir strojnega učenja
PythonPyTorch

Opis

  • 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.

Zahteve

  • 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.

Ugodnosti

  • 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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