Build and scale real-time TTS serving infrastructure for voice AI models, from GPU inference engines to production APIs. Requires hands-on experience with multinode ML serving frameworks, distributed inference, and cloud/SRE practices.
Salary not listed
On-site5+ YOEML Engineering
About the role
What You'll Own
Architecture and implementation of Rime's TTS serving infrastructure, from GPU-backed inference engines to the API surface.
Model optimization from a single-node to disaggregated fleet serving.
Compatibility with different NVIDIA hardwares from Hopper to Blackwell and beyond for on-prem and cloud deployments.
Continuous integration and deployment workflows for the model serving pipeline.
Site reliability: on-call rotation, monitoring, alerting, and observability across the serving stack.
Resource provision, cost management across our GPU fleet.
What We're Looking For
Hands-on experience with real-time multinode ML serving infrastructure — ML serving framework experience: NVIDIA Dynamo/Triton, vLLM, SGLang, or equivalent.
Experience with distributed or disaggregated model serving (Tensor Parallel, Pipeline Parallel, or equivalent).
Strong cloud infrastructure fundamentals: Linux internals, networking, containerization (Docker, Kubernetes).
IaC experience — Terraform, Packer, or comparable.
On-call is part of the job. You treat production reliability as a shared responsibility.
Nice to Have
Experience with multinode training (DDP, FSDP, etc.).
Experience with gRPC or other bidirectional binary streaming protocols.
Experience with audio streaming and related technologies (WebRTC, WebSockets, etc.).
Experience with a multilingual monorepo where you pick the best language out of merit more than personal experience.
Experience with multi-cloud infrastructures (AWS, GCP, OCI, etc.).
Comfort with configuration management tooling (Ansible, Chef, Puppet, or similar).
SRE, DevOps, or platform engineering background at a startup.
Experience at an early-stage company.
Skills
Ml ServingNvidia TritonvLLMSglangTensor ParallelPipeline ParallelLinuxDockerKubernetesTerraformgRPCWebrtcAWSGCP
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