Principal ML Platform Engineer

Responsibilities

• Design and improve the platform systems that support model training, evaluation, and production serving.
• Build infrastructure and tooling that make ML workloads more reliable, scalable, and cost-efficient.
• Develop internal tools and workflows that are easy to operate both by humans and by agents.
• Work on the architecture behind how models are deployed, served, and operated across research and product environments.
• Improve how we schedule, monitor, and debug workloads running on GPUs and cloud infrastructure.
• Develop internal tools and abstractions and agentic systems that reduce operational overhead for researchers and engineers.
• Drive improvements across observability, automation, reliability, and developer experience.
• Collaborate closely with researchers and product engineers to understand pain points and turn them into robust platform capabilities.
• Contribute to technical direction and make pragmatic architectural tradeoffs as the platform grows.
• You’ll thrive in this role if you have

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