Software Engineer, Inference
Pulse, San Francisco
The role
Overview
Pulse is tackling one of the most persistent challenges in data infrastructure: extracting accurate, structured information from complex documents at scale. We have a breakthrough approach to document understanding that combines intelligent schema mapping with fine-tuned extraction models where legacy OCR and other parsing tools consistently fail.
We are a small, fast-growing team of engineers in San Francisco powering Fortune 100 enterprises, YC startups, public investment firms, and growth-stage companies. We are backed by tier 1 investors and growing quickly.
Specialize in low-latency, high-throughput inference for OCR and multimodal models. Own profiling, batching, and autoscaling across single-tenant and multi-tenant environments.
What you will do
- Build inference services with smart batching and caching
- Optimize kernels, tokenization, and model graphs
- Evaluate vLLM, TensorRT LLM, and Triton tradeoffs
- Implement autoscaling and admission control with clear SLOs