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Plato.so
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Applied research lab building simulated training environments for agents1-10 Employees
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Jobs at Plato.so

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Engineering

Member of Technical Staff, Research Scientist - AI Safety & Security

NewPosted 2 weeks ago

Member of Technical Staff, Research Scientist - AI Safety & Security

  • Work with the frontier: Build safety environments and benchmarks that research teams at leading AI labs can use to measure emerging capabilities and misaligned behavior.
  • Real ownership: Help set Plato’s safety evaluation agenda, from the research questions worth testing to the evidence we share with lab partners.
Operations

Member of Technical Staff, Technical Account Manager - Frontier Labs

NewPosted 2 weeks ago

Member of Technical Staff, Technical Account Manager - Frontier Labs

  • Work with the frontier: You will be the day-to-day partner to research teams at the world's top AI labs, running the environment projects that shape how their next models are trained and evaluated.
  • Real ownership: You run projects end to end, from a lab's first spec to final delivery, with a direct line to the founders.
Engineering

Member of Technical Staff, Software Engineer

NewPosted 4 weeks ago

Member of Technical Staff, Software Engineer

  • Develop product surfaces for researchers, domain experts, and customer teams to inspect, tune, replay, and validate generated environments.
  • Build backend systems for trace ingestion, schema handling, environment generation, task generation, scoring, and telemetry.
Engineering

Member of Technical Staff, Research Engineer

NewPosted 4 weeks ago

Member of Technical Staff, Research Engineer

  • Discover model failure modes from real-world traces, agent telemetry, targeted researcher hypotheses, and customer workflows.
  • Generate realistic curricula grounded in actual workflows rather than toy synthetic benchmarks.
Engineering

Member of Technical Staff, Head of AI Quality

NewPosted 4 weeks ago

Member of Technical Staff, Head of AI Quality

  • Own the Ground Truth: You will own the final checkpoint between raw environments and customer model runs. If an environment teaches a model the wrong behavior, you pull the plug.
  • Massive Leverage: We don’t solve quality by throwing armies of manual labelers at a spreadsheet. You will architect the automated judge harnesses, red-teaming agents, and telemetry that enforce quality programmatically.