Founding ML Research Engineer
Hybrid (San Francisco)$180k - $250kFull-timePosted 2mo ago
About the role
Founding ML Research Engineer to work across data, pre-training, post-training and evals for training Generalist Audio Models at Kalpa Labs. Full-stack role with autonomy, focusing on scalable ML systems and productionizing research ideas.
Responsibilities
- Research better multi-modal architectures & codecs that are efficient across both spoken speech & general audio.
- Post-train audio models to have LLM like instruction following & in-context learning but over both text and audio.
- Build large-scale speech model pre-training and post-training (SFT/RLHF-style, distillation, preference optimization, etc.).
- Build scalable data + compute pipelines: dataset curation, filtering, mixing, tokenization/feature pipelines, evaluation harnesses.
Qualifications
- Industry/Academia experience pre-training / post-training large neural networks; speech/audio is a plus but not required, language/vision experience is also relevant.
- Strong ML systems and engineering depth (distributed training, performance, reliability).
- Comfort operating in ambiguity: you can spec, build, debug, and ship.
Skills
Required:Machine LearningDistributed Training
Last updated Oct 21, 2026. Interested? Apply on the company site.
About Kalpa Labs
Frontier Speech models
We're building the next frontier of speech models that can pass the turing test over long conversations along with state-of-the-art infra for your voice agents.
artificial-intelligencespeech-recognitionconversational-ai