Strong backend engineering experience with Python
Experience building and operating distributed, containerized applications, preferably on AWS
Proficiency implementing observability solutions (monitoring, logging, alerting, tracing) for production systems
Ability to design and implement resilient, scalable architectures
Track record of independently scoping and delivering complex technical projects from problem identification through production deployment
Comfort navigating ambiguity and making pragmatic technical decisions when requirements are unclear or evolving
MLOps experience, including familiarity with PyTorch and Kubernetes
Experience working in fast-paced environments where you owned technical direction for an area and drove projects with minimal oversight.
Experience collaborating with remote, globally distributed teams
Comfort working across the entire ML lifecycle from model serving to API development
Experience in audio-related domains (ASR, TTS, or other domains involving audio processing)
Experience with other cloud providers
Familiarity with Bazel and monorepos
Experience with alternative ML inference frameworks beyond PyTorch
Experience with other programming languages
Experience mentoring junior engineers or onboarding teammates onto complex systems

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