Machine Learning Engineer
Hybrid (San Francisco)$160k - $220kFull-timePosted 11mo ago
About the role
Pulse is building production-grade, unstructured document extraction with a multi-stage architecture combining layout understanding, OCR, reading order, table structure parsing, and vision-language models. The role focuses on creating specialized vision and language models to power Pulse, with autonomy to train, fine-tune, and ship production improvements.
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
Qualifications
- 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
Skills
Required:Applied machine learning / researchPyTorch or JAXVision / multimodal architectures
Benefits
- Competitive base salary plus equity
- performance-based bonus
- relocation assistance for Bay Area moves
- daily meal stipend
- medical, vision, and dental coverage
Last updated Sep 16, 2026. Interested? Apply on the company site.
About Pulse
Production-grade unstructured document extraction
Pulse converts complex information into LLM-ready inputs. Our API supports all document formats, from PDFs to Word, Excel, etc. Pulse integrates seamlessly with any existing data pipeline in minutes without any training or complexity.
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