Job Description

Location: San Francisco or Remote (U.S.)

Rime builds enterprise-grade voice models that sound truly human — trusted by global telcos, healthcare systems, and leading brands to power billions of real customer interactions. Our mission is to set the standard for natural, controllable, and privacy-preserving voice AI.

We’re an early-stage team backed by top investors, growing quickly as enterprises adopt AI voice across customer experience, automation, and accessibility use cases.

We’re looking for a Model Deployment Engineer to bridge the gap between Rime’s cutting-edge voice models and our enterprise customers. You’ll be responsible for designing, deploying, and optimizing Rime’s on-prem and VPC implementations , ensuring our technology runs seamlessly inside complex enterprise environments.

This is a hands-on, customer-facing technical role — part Sales Engineer, part Forward Deployed Engineer. You’ll work closely with our Sales, Product, and Infrastructure teams to design solutions, troubleshoot deployments, and make sure our customers see value from day one.

• Partner with Sales to scope and architect deployments for enterprise customers (on-prem, VPC, or hybrid).
• Deploy and configure Rime’s inference runtimes , integrate APIs, and optimize GPU and network performance.
• Build reference deployments, automation scripts, and Helm templates to streamline future implementations.
• Train customer technical teams on deployment management, scaling, and observability best practices.
• Act as the technical voice of the customer , providing structured feedback to Rime’s Product and Engineering teams.
• Troubleshoot performance issues, manage escalations, and ensure high uptime and reliability post-launch.

• 6+ years in Sales Engineering, Solutions Architecture, Forward Deployed Engineering, or DevOps roles supporting enterprise AI/ML systems.
• Experienced with AI/ML inference workloads in on-prem, private cloud, or hybrid environments.
• Proficient with Kubernetes, Docker, Helm , and major cloud providers ( AWS, GCP, Azure ).
• Familiar with TTS or LLM inference , GPU optimization, and model-serving frameworks.
• Strong communicator who can translate between enterprise IT, AI engineering, and business stakeholders .
• Thrives in an early-stage environment and loves rolling up your sleeves to make deployments work in production.

• Be part of a team defining how enterprises adopt and deploy AI voice technology at scale.
• Work directly with world-class engineers, linguists, and founders at the forefront of speech AI.
• High ownership, zero bureaucracy, and the chance to build the deployment playbook for a fast-growing category leader.
• Competitive compensation package, equity, and the opportunity to shape the future of AI voice infrastructure.

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