Machine Learning Research Intern, Audio

The Role

The Role: Machine Learning Research Intern, Audio

What You Will Do

• Own a research question end to end
• Take one well-scoped problem from literature review through implementation, experimentation, and results
• Design ablations that isolate what actually caused an improvement
• Present your findings to the research team and defend the methodology
• Work on real systems
• Train and evaluate models on large-scale, real-world telephony audio, including the accents, noise, and artifacts that make production speech hard
• Use our distributed GPU infrastructure rather than toy-scale setups

Where the result warrants it, work with engineers to move it toward production

Choose your depth

• Depending on your background and interests, your project may focus on:
• Expressive and controllable text-to-speech, including prosody and emotion modeling
• Natural language understanding and generation
• Neural audio codecs and discrete or continuous speech representations
• ASR robustness for telephony, accents, and code switching
• Real-time and streaming inference under latency constraints
• Full-duplex conversation and turn-taking dynamics

What Makes You a Great Fit

• Research foundations
• Currently pursuing a MS or PhD in ML, CS, EE, or a related field, or equivalent research experience
• Comfortable reading a paper and reimplementing it without hand-holding
• Experience with self-supervised, generative, or multimodal modeling
• Audio or speech grounding
• Hands-on work with speech or audio models, whether TTS, ASR, codecs, or audio representation learning
• Strong intuition for audio quality and what makes synthetic speech sound wrong
• Prior publications or open source contributions in speech or language AI are a strong signal, though not required
• Engineering ability
• Fluent in PyTorch and comfortable in a real codebase
• Able to run your own experiments on GPU clusters without waiting to be unblocked

How You Show Up

• You identify the single experiment that validates an idea in days, not months
• You measure everything and let data drive decisions
• You are honest about negative results, because they are how we narrow the search
• You are obsessed with making voice agents sound truly human
• You use AI tools aggressively to amplify your own impact

Benefits

• Competitive intern compensation
• Mentorship from researchers working on frontier voice AI
• Every tool you need to succeed
• A beautiful office in Levi's Plaza, SF with rooftop views
• A real shot at a return offer