Want to own the data infrastructure behind some of the most naturalistic voice models in production?

You'll be joining a well-funded speech AI startup — just closed their Series A — with strong enterprise traction and revenue that more than doubled last quarter. They're building ultra-realistic voice technology that handles natural laughter, breathing, seamless language switching, and accurate pronunciation across languages and accents. Their models are powering hundreds of millions of conversations monthly.

Before training a single model, they built their own corpus — full-duplex, studio-quality conversational speech annotated by PhD linguists. As their MLE, you'll own the pipelines that turn that raw material into clean, training-ready data.

What you'll do

• Own end-to-end data pipelines from raw audio ingestion through to versioned, training-ready datasets
• Build quality systems that catch annotation errors and alignment issues before they reach a training run
• Maintain the training infrastructure that keeps GPUs fed — dataloaders, streaming datasets, multi-modal batching
• Build and iterate on tooling across speech representations including neural codecs, semantic tokens and mel features
• Handle full- and half-duplex pipeline work including two-channel alignment and overlap handling

What you'll bring

• Strong engineering fundamentals with experience building ML data pipelines at scale
• Hands-on experience with speech or audio data
• Solid understanding of speech representations and the tradeoffs between them
• Experience with multi-channel audio data including diarisation and alignment

Nice to have

• Experience with multilingual data pipelines
• Large-scale training infrastructure experience — FSDP, DeepSpeed, Ray
• Annotation tooling and human-in-the-loop systems

Remote-friendly. Competitive base plus stock.

Want to build speech AI that actually sounds human?

You'll be joining a well-funded speech AI startup with strong customer traction. They're building ultra-realistic voice technology that handles natural laughter, breathing, seamless language switching, and accurate pronunciation across languages and accents.

As their Senior Research Scientist, you'll work hands-on to expand their foundation models and push the boundaries of what's possible in speech AI: exploring multilingual capabilities, long-context generation, full-duplex modeling for natural conversations with interruptions, and novel architectures that balance speed with control.

What you'll do

• Conduct research to advance their core speech models and extend product capabilities
• Develop and experiment with new model architectures and training approaches
• Work on large-scale model training and data systems
• Collaborate with the team to take research from concept to deployed systems

What you'll bring

• 3+ years of experience in speech synthesis, audio generation, or generative modeling
• Experience with audio generation using LLMs
• Solid background in modern language model architectures
• Proven ability to ship research into production systems
• Experience training large-scale models

Nice to have

• Published research in speech or generative modeling
• Experience with real-time speech systems or multimodal models

Ideally in SF, but can also consider remote worldwide. Comp is up to $250K base DOE, plus equity.

Build speech AI at trillion-parameter scale, driving human to AI conversation

This team has built their entire speech stack in-house, including proprietary LLM-based ASR and TTS, both already outperforming SOTA benchmarks. It's already powering real-time, human-to-AI conversations at scale, every day.

Now they're working at trillion-parameter scale to push toward a genuine end-to-end speech-to-speech LLM, one that understands and responds with genuine emotional intelligence and natural, human-like conversation. That means solving problems like long-context reasoning, pronunciation accuracy and maintaining consistency in noisy, real-world environments, in a domain where no model has cracked this yet.

They're hiring Senior and Staff-level Speech Scientists (Principal-level also considered) to help drive that work.

What you'll do:

• Build SOTA speech models from the ground up, at genuinely large scale
• Own problems end-to-end, from research through to production
• Solve hard, domain-specific speech challenges as part of the push toward speech-to-speech LLM research
• Help shape technical direction as part of a team working at the frontier of this space

What you'll bring:

• Deep, hands-on expertise in at least one of: Speech/Audio LLMs, TTS or audio generation, or large-scale speech understanding
• Experience shipping speech systems at real scale, not just research-stage prototypes

Nice to have:

• Experience pre-training speech foundation models (HuBERT, Wav2Vec or similar)
• Multimodal experience

Package: Up to $350K–$400K base (DOE), plus substantial equity. On-site, South Bay or Seattle.