Machine Learning Engineer

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 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.

What we are 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

About the Role

Create the specialized vision and language models that power Pulse. You will have autonomy to train and fine-tune models and to ship improvements to production.

Responsibilities

Train and fine tune OCR, layout, table, and vision-language models

Build evaluation, data curation, and active learning pipelines

Optimize inference, batching, and quantization on GPU

Productionize models with clear SLAs and rollback plans

Write internal notes that inform model and product roadmaps

Requirements

3+ years in applied ML or research, or strong open source record

PyTorch or JAX, and modern vision or multimodal architectures

Solid engineering discipline and metrics focus

Nice to have

Triton Inference Server, TensorRT, ONNX, distributed training

Sponsorship

Sponsorship available.

Compensation and benefits

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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