Founding ML Infrastructure Engineer

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. Speech/audio experience is a plus, not required.