Founding ML Research Engineer - Training Infrastructure (San Francisco)
Kalpa Labs (YC F25)
Join to apply for the Founding ML Research Engineer - Training Infrastructure role at Kalpa Labs (YC F25)
This range is provided by Kalpa Labs (YC F25). Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
$140,000.00/yr - $200,000.00/yr
We’re hiring a Founding ML Research Engineer to build the pre-training and post-training infrastructure for training some of the largest speech models in the world. You’ll own the training stack end-to-end with a small team, tons of compute, high autonomy, and the mandate to push toward 100B+ scale as we scale generalist speech models.
What You’ll Do
- Design and implement a production-grade training stack for 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, and experiment tracking.
- Own distributed training: performance profiling, stability, fault tolerance, checkpointing, resumption, and high-throughput I/O.
What We’re Looking For
- Strong ML systems and engineering depth (distributed training, performance, reliability).
- Practical experience training large models (speech/audio is a plus but not required; language/vision experience is also relevant).
- Comfort operating in ambiguity: you can spec, build, debug, and ship.
To apply
Reply with your best paper / blog post / arXiv link and a short note on what you built and what you want to build next.
Seniority level
Entry level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Technology, Information and Media
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