About the role

Nanonets has a vision to automate the most complex, time-consuming processes inside companies which take away hours of valuation time from employees. Our workflow automation platform is powered with the latest models that can make sense of even unstructured data like documents.

Our client footprint spans across brands such as Toyota, Boston Scientific, Bill.com and Entergy to name a few enabling businesses across a myriad of industries to unlock the potential of their visual and textual data.

Some of the technical challenges we deal with are fine-tuning SOTA VLM’s for workflow automation, using generating architectures for their superior emergent behaviour to understand the world but also constraining those architecture to reduce hallucination and generate structured workflows which can be used in completely automated manner.

We recently announced a series B round of $29 million in funding by Accel and are backed by the likes of existing investors including Elevation Capital & YCombinator. This infusion of capital underscores our commitment to driving innovation and expanding our reach in delivering cutting-edge AI solutions to businesses worldwide.

Read about the release here:

https://www.forbes.com/sites/davidprosser/2024/03/12/why-enterprises-are-learning-to-love-nanonets-automation/?sh=6d79ec8f3ca1

https://techcrunch.com/2024/03/12/nanonets-funding-accel-india/amp/

What We Expect From You

Strong Machine Learning & DL concepts.
Strong command in low-level operations involved in building architectures like Transformers, Efficientnet, ViT etc., and experience in implementing those in pytorch/jax/tensorflow.

AI agents break where it matters most: when the details are buried in an invoice, a BoL, or a clinical document. Most agents guess. They hallucinate field values, apply rules inconsistently, and when something goes wrong, you can’t tell why or fix it without redoing the work yourself.

Nanonets is built differently. Every extraction is traceable. You can see exactly what the agent read, what rule it applied, and why it made the call it did. When it’s uncertain, it flags the right thing for human review instead of silently getting it wrong. When you correct it, it learns. When you add business rules, it tracks which rule drove which decision.

Anyone can build agentic workflows, but AI agents are black boxes that struggle with complex files and processes, like POs, invoices, BoLs and clinical documents. Nanonets agents understand key details in files, work through complex processes and act with transparency, making them the most reliable foundation for building workflows where details matter.

Nanonets reduces processing time by 95% by automating messy manual processes and delivering clean data to systems of record like SAP, SFDC and more. That’s why Nanonets is the automation layer global enterprises reach for when accuracy is non-negotiable.

VP of AI

About the role

What We Expect From You

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