--- title: "Software Engineer, ML Serving - Rime Ai" company: "Unusual" company_url: "https://www.remjobs.works/companies/unusual" url: "https://www.remjobs.works/job/unusual-software-engineer-ml-serving-rime-ai-8d730440-aeeb-4ba1-9d1f-2b30cc4602c1" apply_url: "https://jobs.lever.co/unusual/ef80001d-bc4a-44e6-968c-d7270f80b618" workplace: onsite location: "San Francisco, California" employment_type: full-time seniority: mid role: ai-machine-learning region: united-states skills: ["aws", "docker", "gcp", "kubernetes", "linux", "terraform"] date_posted: 2026-06-24T22:08:21.551Z first_seen_by_remjobs: 2026-08-27T09:28:16.971Z --- # Software Engineer, ML Serving - Rime Ai **Unusual** — San Francisco, California Apply: https://jobs.lever.co/unusual/ef80001d-bc4a-44e6-968c-d7270f80b618 ## About Unusual AI agents are the newest audience brands need to speak to, but go-to-market teams don't have the tools to understand how they form opinions or make decisions. Unusual helps brands in the Fortune 100 and scale-ups like Change.org and Astronomer drive more sales and win more market share by shifting how AI models perceive their offerings. We work closely with every brand to (1) identify the root cause of AI misperception, (2) align on marketing, sales, and product strategies that appeal to agents, and (3) build infrastructure and content that makes their strongest proof more legible to agents. Our methodology centers on applying black-box interpretability techniques to AI agents like ChatGPT and Claude to understand how they form opinions about a brand and its competitors. Seeing the *why* behind each opinion gives us the ability to create targeted interventions that change them. ## About the role 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. It's why our models are unparalleled in naturalism, and it's why enterprises pick Rime when pilots need to make it to production. **Role Overview** We're hiring a Software Engineer to own the serving infrastructure that connects Rime's inference engines to the world. This role sits at the intersection of ML systems and cloud infrastructure — you'll 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, you'll be a core architect of how our models get served. ##### 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. 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 it'll lead to making money If that sounds like you too, you'll be a great fit for Rime! --- Source: Unusual's own career page, read by RemJobs. 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