PrimelabsAbout this role
Summary: Advance audio capabilities for AI-native education by researching and developing models that capture nuanced pronunciation details and provide real-time conversational feedback. The role involves designing experiments, writing high-performance code, and collaborating with research engineers to ship improvements t...
About Prime Labs
We are a small research lab building foundation models for AI-native education products, starting with English language learning. Our mission is to empower hundreds of millions of children worldwide with AI that understands how they actually speak, identifies and corrects pronunciation errors, provides phoneme-level feedback, adapts to their proficiency, and knows how to help them make progress. Our models are trained on millions of hours of proprietary, one-of-a-kind data from authentic one-on-one lessons between teachers and children, collected over many years of one-on-one teaching at a massive scale and analyzed with the rigor of a research lab. We are backed by DST Global, Reach Capital, K3 Ventures, and others.
About the Team
Our research team brings together AI researchers, learning scientists, veteran educators, and Stanford faculty with a remarkable breadth of experience, from scaling a business to $1B in revenue, to developing the open-source VibeVoice model at Microsoft, developing TeachLM, and working on large-scale scientific computations at Harvard and MIT.
About the Role
As a Senior Research Scientist at Prime Labs, you will advance the frontier of audio capabilities for education. You'll explore how audio models can capture nuanced details of children's English pronunciation, identify articulation errors that off-the-shelf models miss, and respond with appropriate teacher-like prosody that helps students recognize and correct their mistakes while keeping them engaged and motivated to learn. You'll also help our models hold natural, real-time conversations: knowing when to listen, when to speak, and how to respond with low latency.
You will be exploring uncharted territory in both the audio and pedagogical domains. This is an opportunity to shape the fundamental capabilities of AI models that will power the learning of millions of students through a large and established distribution channel spanning many countries.
This role blends fundamental research and practical engineering; everyone here does both. You'll be expected to read cutting-edge papers, develop new approaches, write high-performance code, and rigorously evaluate your ideas through experiments. It's an excellent fit for someone who enjoys both deep theoretical exploration and practical experimentation, and wants to shape the future of how AI teaches and how students learn.
What You'll Do
- Identify high-leverage research problems across our model development pipeline (data pre-processing, modeling and evaluation) and take full ownership of driving them forward
- Design and run rigorous experiments, then translate what works into shipped improvements to our models and live products
- Work directly with research engineers to move fast from prototype to production
- Help set the scientific direction of the team and raise the bar on how we do research
What You'll Bring
- A track record of original research: you've found a real problem, developed a novel approach, and seen it through
- Deep expertise in at least one of: speech synthesis, ASR, or speech-to-speech models
- Experience training large models: PyTorch, distributed training, and large audio datasets
- Ability to design, run, and analyze experiments thoughtfully, with demonstrated research judgment and empirical rigor
- Fluency in probability, optimization and linear algebra, and the ability to reason about model behavior from first principles
- You move fluidly between ideas and implementation; you don't just write papers, you build things
- Clear, precise written and verbal communication
Nice to Have
- Publications, model releases, or open-source contributions in speech, audio, voice, or related areas
- Hands-on experience with neural audio codecs, autoregressive audio modeling, or speech-language models
- A PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related field, or equivalent industry research experience, with a strong foundation in both theory and empirical experimentation
What We Offer
- A one-of-a-kind educational data corpus with millions of hours of authentic teacher–child conversations
- Real ownership within a small team where your work shapes the whole model
- Dedicated GPU capacity for large-scale training
- Impact you can see: your model teaches real children within months
- Competitive base salary alongside an attractive equity package
Logistics
- Location: on-site in Palo Alto, CA
- Global team: we are a global team with offices in California, Budapest (Hungary) and Singapore. We collaborate in person through frequent travel to and from California.