Pulse Supply Chain Solutions
From Pulse Supply Chain Solutions's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
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.
What makes our tech special https://www.runpulse.com/blog/pulse-approach-to-document-intelligence is our multi-stage architecture:
Layout understanding with specialized component detection models
Low-latency OCR models for targeted extraction
Advanced reading-order algorithms for complex structures
Proprietary table structure recognition and parsing
Fine-tuned vision-language models for charts, tables, and figures
If you are passionate about the intersection of computer vision, NLP, and data infrastructure, your work at Pulse will directly impact customers and shape the future of document intelligence.
5 days in-office at our San Francisco office
Eager to learn and adapt quickly
Prior startup or founding experience is a plus
5 days in-office at our San Francisco office
Eager to learn and adapt quickly
Prior startup or founding experience is a plus
Specialize in low-latency, high-throughput inference for OCR and multimodal models. Own profiling, batching, and autoscaling across single-tenant and multi-tenant environments.
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
Own performance dashboards and capacity planning
3+ years in performance engineering or ML systems
Strong Python, plus C++ or CUDA exposure
Experience with GPU profiling and model serving
Nice to have
Experience reducing p95 and cost in production ML systems
Competitive base salary plus equity, performance-based bonus, relocation assistance for Bay Area moves, daily meal stipend, medical, vision, and dental coverage.
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