Rime is a foundation modeling company that builds voice AI for enterprises running customer experiences at scale. Our models are purpose-built for high-volume conversational deployments engineered for the accuracy performance and deployment flexibility that production environments actually demand.
We started from a different premise than the rest of the field: build voice AI for human connection not slop. Before we trained a single model we built our own corpus: full-duplex studio-quality conversational speech of normal people recorded and annotated by linguists. Its why our models are unparalleled in naturalism and its why enterprises pick Rime when pilots need to make it to production.
Role Overview
Were hiring a Software Engineer to own the serving infrastructure that connects Rimes inference engines to the world. This role sits at the intersection of ML systems and cloud infrastructure youll work directly on model inference and cloud infrastructure to build harden and scale the systems that stream voice at real-time latency. As Rime moves toward its next-generation architecture youll be a core architect of how our models get served.
What Youll Own
Architecture and implementation of Rimes 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 Were 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. You should have opinions about how to do this right.
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.
Why Join Rime
Build the serving infrastructure behind a category-defining voice AI company from the ground up.
You will bring in experience that no one else currently has at the company: you can help us set the vision.
Direct collaboration with the inference platform and ML teams no handoff culture.
The systems you build determine what experiences our customers can deploy at scale.
Meaningful equity upside at an early stage.
High ownership high standards low bureaucracy.
SF / Bay Area.
At Rime we...
Are outliers
Cut through the hype to focus on the craft
Move fast with agency and freedom
Maintain a growth mindset finding joy in the struggle
Do the right things knowing that itll lead to making money
If that sounds like you too youll be a great fit for Rime!
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
Required Experience:
IC
Rime is a foundation modeling company that builds voice AI for enterprises running customer experiences at scale. Our models are purpose-built for high-volume conversational deployments engineered for the accuracy performance and deployment flexibility that production environments actually demand.We...
Rime is a foundation modeling company that builds voice AI for enterprises running customer experiences at scale. Our models are purpose-built for high-volume conversational deployments engineered for the accuracy performance and deployment flexibility that production environments actually demand.
We started from a different premise than the rest of the field: build voice AI for human connection not slop. Before we trained a single model we built our own corpus: full-duplex studio-quality conversational speech of normal people recorded and annotated by linguists. Its why our models are unparalleled in naturalism and its why enterprises pick Rime when pilots need to make it to production.
Role Overview
Were hiring a Software Engineer to own the serving infrastructure that connects Rimes inference engines to the world. This role sits at the intersection of ML systems and cloud infrastructure youll work directly on model inference and cloud infrastructure to build harden and scale the systems that stream voice at real-time latency. As Rime moves toward its next-generation architecture youll be a core architect of how our models get served.
What Youll Own
Architecture and implementation of Rimes 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 Were 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. You should have opinions about how to do this right.
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.
Why Join Rime
Build the serving infrastructure behind a category-defining voice AI company from the ground up.
You will bring in experience that no one else currently has at the company: you can help us set the vision.
Direct collaboration with the inference platform and ML teams no handoff culture.
The systems you build determine what experiences our customers can deploy at scale.
Meaningful equity upside at an early stage.
High ownership high standards low bureaucracy.
SF / Bay Area.
At Rime we...
Are outliers
Cut through the hype to focus on the craft
Move fast with agency and freedom
Maintain a growth mindset finding joy in the struggle
Do the right things knowing that itll lead to making money
If that sounds like you too youll be a great fit for Rime!
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
Unusual Ventures is raising the bar for what founders should expect from their venture investors and enabling startups with the support they need to be successful.
Job Location:
Monthly Salary:
Posted on:
Vacancies:
