Pulse
Production-grade unstructured document extraction
$150K - $250K / 0.50% - 2.50%
Location
San Francisco, CA, US
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About the role
As a Machine Learning Engineer at Pulse, you'll create the specialized vision and language models that form the backbone of our document understanding capabilities. You will be given research autonomy for training and fine-tuning these models.
About Pulse
At Pulse, we're tackling one of the most persistent challenges in data infrastructure - extracting accurate, structured information from complex documents at scale. We've developed 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're a small but fast-growing team of engineers based in San Francisco, working on technology that's powering Fortune 100 enterprises, YC startups, public investment firms, and growth-stage companies. We're backed by tier 1 investors and are growing fast.
What makes our tech special is our multi-stage architecture approach to document intelligence:
- Layout understanding with specialized component detection models
- Low-latency OCR models for targeted extraction
- Advanced reading order algorithms for complex document structures
- Proprietary table structure recognition and parsing
- Fine-tuned vision-language models for charts, tables, and figures
If you're passionate about solving complex challenges at the intersection of computer vision, NLP, and data infrastructure, you'll find that at Pulse, your work directly impacts customers and shapes the future of document intelligence.
What Are We Looking For?
- 5 days in-office at our San Francisco office
- Eager to learn and adapt quickly
- Prior startup or founding experience is a plus
Compensation
- Competitive base salary plus equity
- Performance-based bonuses
- Relocation assistance for Bay Area moves
- Daily meal stipends
- Comprehensive medical, vision, and dental coverage
Pulse
Founded:2024
Team Size:4
Status:Active
Founders