Data Engineer

Nanonets has a vision to help computers see the world starting with reading and understanding documents. Our product helps businesses automate document related workflows for enterprise office teams such as invoice data entry for AP teams, KYC automation for banks and insurance etc. Some of the companies we work with include Toyota, Boston Scientific, Bill.com and Entergy to name a few.

We recently raised a series B round of $29 million. Now we’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity.

Nanonets is proud to be an equal opportunity workplace dedicated to pursuing, hiring, and retaining a diverse workforce.

About the Role

We are seeking a motivated and adaptable AI Data Engineer with a strong interest in data infrastructure. This role will play a crucial role in scaling data sets that we use for training our AI models. The ideal candidate will be passionate about building robust and efficient data pipelines, ensuring data quality, and contributing to the advancement of our AI capabilities.

Responsibilities:

A] Large scale data collection (in millions) by -

a. Either web scraping existing open datasets.

b. Or Nanonets internal dataset using our apis.

B] Dataset filtering, cleaning and validation -

a. Using foundational models or rule based methods to filter out dataset.

b. Working on data visualisation tools like streamlit/gradio.

C] Run existing benchmarks on models.

D] Model migration: based on benchmark migrate models from older models to new models.

E] Coordinate with annotators.

Qualifications:

• B.E/B.Tech from a reputed school.
• 0-3 years of experience.
• Strong hands-on experience in Python
• Good written and verbal communication skills.
• Strong interpersonal skills, with the ability to build rapport.

Thinking of applying? Try our resume builder— it's free, fast, and tailored to help you stand out.