We’re hiring a Founding ML Infrastructure Engineer in Bengaluru to own the systems that train and serve our Speech models: the distributed training stack, Realtime inference engine, and the cloud services. You’ll work in a small team with tons of compute and see your ideas making it to production in days.
What You’ll Do
Own the training stack: FSDP/HSDP and Megatron-style tensor parallelism in our PyTorch framework
Make realtime inference fast: time-to-first-audio and throughput on our vLLM-based engine, Quantization, model compilation and load testing under high concurrency.
Build data pipelines at scale: Work on creating in-house data pipelines that process Millions of hours of audio and feed training at high throughput.
Run the production path: API gateway and streaming WebSocket APIs, deploy tooling, logging, monitoring.
What We’re Looking For
3+ years building ML systems or high-performance backend infrastructure.
Hands-on depth in at least one of: distributed training (FSDP/TP/PP), LLM serving (vLLM/SGLang/TensorRT-LLM), High volume data processing, or low-latency streaming systems.
Comfort operating in ambiguity: you can spec, build, debug, and ship.
How do I apply for the Founding ML Infrastructure Engineer job at Kalpa Labs (YC F25)?
Use the apply link on this page: you apply directly with Kalpa Labs (YC F25) on LinkedIn. Before you do, score your resume against this job description on Fitboard. It shows which skills and keywords the job asks for that your resume doesn't show, so you can fix them first.
What skills does Kalpa Labs (YC F25) want for this Founding ML Infrastructure Engineer role?
The job description asks for FSDP, HSDP, Megatron-style tensor parallelism, PyTorch, vLLM, Quantization, model compilation and API gateway. Make sure your resume shows the ones you have, in the words the job uses: applicant tracking systems look for them.
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Is this Founding ML Infrastructure Engineer job remote or onsite?
This is based in Bengaluru, Karnataka.
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