Experience Not stated in the posting - worth applying if the stack matches
About the role
structured by ORIKalpa Labs · F25 # Founding ML Research Engineer Scaling Generalist Speech models LocationSan Francisco, CA, US TypeFull-time Salary$180K - $250K Equity0.50% - 1.00% Experience3+ years VisaWill sponsor Machine Learning Apply to this role About the role We’re hiring a Founding ML Research Engineer to work work through…
What you will do
- 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.
- Look at lots of data & hear lots of audio.
What they are looking for
- 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.
- A hunger to always ask - what would the next frontier look like?
Nice to have
- Speech/audio experience is a plus.
Before you apply
- To apply: Share arxiv links to papers that you co-authored, you enjoyed reading, or you found surprising.
Machine Learningpre-trainingpost-trainingLLMdistributed trainingSFTRLHFdistillation
Full posting text
Help push the frontier of speech models.