Research Engineer

Phonic is a product and research lab focused on powering the most realistic, human-like voice AI conversations. We've re-thought the entire stack in pursuit of this goal, from models to product, to create voice agents that feel like they truly understand you, respond emotionally and perform agentic tasks with frontier intelligence.

Our team includes top-tier AI researchers, international olympiad medalists, and former founders.

Our customers include companies that are building voice-native AI products in industries such as customer support, healthcare, and logistics. We have raised over $30M from tier 1 VCs.

Phonic has a very talent-dense and close-knit team. We collaborate with high trust and are constantly trying to improve how we work to deliver world-class research and product. Everyone takes ownership in what they do and they aren’t afraid to dive in headfirst into new problems. Our team includes top-tier AI researchers, international olympiad medalists, and former founders and we’re fully in-person in our SF office.

As a Research Engineer at Phonic, you'll sit at the intersection of cutting-edge ML research and production engineering, working directly on the core systems that make Phonic's voice AI feel genuinely human. You'll design, train, and iterate on models across the voice stack (speech, audio, language, and beyond), while also building the infrastructure and tooling needed to move fast from research idea to deployed product.

This is a role for someone who thrives in ambiguity, moves with urgency, and takes full ownership of problems. You'll work closely with researchers and product engineers in a high trust, in-person environment in our SF office to push the frontier of what voice AI can do.

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  Design, implement, and iterate on models across the voice stack from audio and speech to language and beyond

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  Build the training pipelines, evaluation frameworks, and tooling that let us experiment and iterate quickly

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  Translate research results into production-grade systems alongside our engineering team

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  Form hypotheses, chase down interesting results, and take ownership over the problems you work on

• Hands-on experience in ML research or research engineering, industry or PhD-level academia

• Proficiency in Python and PyTorch (or JAX), and the ability to implement models cleanly from papers

• Experience running ML experiments end-to-end: data processing, training, evaluation, and iteration

• Comfort in fast-moving, ambiguous environments - defining the problem is part of the job

• The ability to clearly explain what you tried, what worked, and why

• Research experience in speech, audio, or language modeling (ASR, TTS, LLMs, codec models)

• Familiarity with diffusion, flow matching, or autoregressive generative models

• Experience with distributed training, quantization, or inference optimization

• Competitive programming or olympiad background