Member of Technical Staff
Phonic
ABOUT PHONIC
Phonic is the speech-to-speech model company. Our mission is to make speaking with agents delightful, and we believe that requires models that hear and answer in native audio. To make that possible in production, we work on every layer of the stack: data, pre-training, post-training, kernels, and infrastructure. We’ve raised over $30M from top-tier investors, including First Round, Lux Capital, and Felicis. Our models power voice agents on six continents for companies like Ashby, Maven AGI, and a Fortune 50 IT infrastructure company, handling everything from customer support and patient intake to recruiting interviews and dispatch.
ABOUT THE TEAM
We’re a small team of researchers and engineers from MIT, Stanford, CMU, MosaicML, Citadel, and Genesis Therapeutics, including former founders, an IMO medalist, and an International Linguistics Olympiad medalist. We work in person in San Francisco five days a week. Everyone here is unusually obsessed with our customers: we’ll happily spend hours perfecting the way our model reasons while it talks, or the way it makes a caller feel heard, going as deep into the stack as it takes.
THE ROLE
As a Member of Technical Staff at Phonic, you'll work across the full range of what it takes to build voice AI from low-level platform and infrastructure engineering to applied research. This is a generalist role: you'll move fluidly between problems as the company needs them solved, taking end-to-end ownership from design through production. We don't divide MTS by title or seniority. You'll be trusted with real scope from day one, and the shape of your role will grow and shift as Phonic does.
WHAT YOU'LL DO
• Own problems end-to-end
• from architecture and design through shipping and iteration in production.
• Work anywhere across the stack as needed: platform and infrastructure engineering, backend services and APIs, product surfaces, or applied research.
• Partner directly with research and ML to translate frontier voice AI capabilities into reliable, production-grade systems.
• Help set technical standards and practices for the team while we're still small enough for it to matter.
• Work wherever your strengths and interests point — infra one week, a research prototype or a customer-facing feature the next; tell us where your interests lie and we’ll help place you there.
WHAT YOU'LL BRING
• Bachelor's degree (or higher) in Computer Science from a top university.
• Proven track record: you've built and shipped production systems you're genuinely proud of.
• Genuine interest and demonstrated ability to work across the full range from platform engineering to research — not boxed into one layer of the stack.
• Strong engineering fundamentals: clean, testable, maintainable code, even when moving fast.
• Full-stack fluency: experience with or strong interest in frontend, backend, infrastructure, and the seams between them, or demonstrably fast at picking up new stacks.
• Ownership mindset: you take problems from ambiguous to shipped without needing a fully-scoped spec.
• Execution speed: you ship, learn, and iterate quickly rather than overplanning.
• Autonomy: you thrive with real scope and minimal oversight, and you're comfortable being opinionated.
• AI-native: you use modern AI tooling (coding agents, LLM APIs) as a natural extension of how you build.
NICE TO HAVE
• Experience with real-time or streaming systems (WebSockets, WebRTC, audio/media pipelines).
• Experience at an early-stage startup where you helped set technical standards.
• Familiarity with voice, telephony, or conversational AI products.
• You're a former founder or technical lead.
BENEFITS
- 💸 Top-tier compensation: in order to get the best talent, we provide salary and equity that recognize your skillset
- 🥗 Meals: free breakfast, lunch, and dinner provided in the office
- 🩺 Healthcare: Comprehensive health, dental, and vision
- 🤝 We have regular off-sites and team celebrations
- 👵 401(k) – Let us help you plan for the future
This job was verified from Ashby (US). Applications are completed on the original source.
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