Software Engineer, Numbers Station

$125-160k

Plus equity

React

TypeScript

JavaScript

Python

Django

Redis

Postgres

Celery

FastAPI

Junior and Mid level

San Francisco Bay Area

Office located in Menlo Park, CA

AI data workflow automation

Be an early applicant

AI data workflow automation

1-20 employees

B2BArtificial IntelligenceEnterpriseData IntegrationAutomation

Be an early applicant

$125-160k

Plus equity

React

TypeScript

JavaScript

Python

Django

Redis

Postgres

Celery

FastAPI

Junior and Mid level

San Francisco Bay Area

Office located in Menlo Park, CA

1-20 employees

B2BArtificial IntelligenceEnterpriseData IntegrationAutomation

Company mission

To enable data practitioners of all skill levels to rapidly automate workflows in the modern data stack using natural language.

Job

Company

Role

Who you are

Self-motivation, enthusiasm, positive attitude, and a growth mindset
Strong technical communication skills
Strong coding skills and knowledge of data structures and algorithms
Ability to work in a fast-paced environment and navigate ambiguity
2+ years of professional experience with scalable web applications

Desirable

Skilled with Python and familiar with web frameworks (FastAPI, Django), ORMs and databases (SQLAlchemy, Postgres) and other common tools (Celery, Redis, pytest)
Familiarity with Javascript or Typescript and React (Remix)
Skilled in writing and deploying integration and unit tests within CI/CD

What the job involves

As a Software Engineer you’ll deliver features that power and enable enterprises to leverage Numbers Station’s technology
With a combination of a user-focused mindset and strong programming skills, you will have full ownership and responsibility for building, shipping, and maintaining innovative new functionality across the stack
Design and develop scalable backend systems, build robust APIs and integrate with frontend applications
Engage with and build solutions for our customers, iterating to balance innovative research with practical solutions
Work with designers and ML experts to create a phenomenal user experience
Ensure code quality and standards through regular reviews and feedback and tests

Our take

Data teams face a difficult task, with the data they need for their analytical work entered messily, located incorrectly or stuck in disconnected silos around the business. Before they are able to begin to work with data it has to be cleaned and reorganized manually, wasting vast amounts of time and resources. Enter Numbers Station, an AI-powered data stack automation tool which uses the latest developments in AI to clean and organize a company's data in a fraction of the time.

At a time when a lot of AI talent is focusing on content generation, Numbers Station is virtually alone in applying the technology to data cleaning, where the problems are just as difficult to solve even if they can't create exciting headlines. This means it's in a strong position to build a market-leading company in this space while helping its customers make better use of their data.

Funding will allow the company to further develop its product and hire additional talent. In the longer term, the company intends to move beyond data preparation to data analysis, allowing it to grow into an essential component in the data stacks of future enterprises.

Steph

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 3 rounds)

Mar 2023

$12.5m

SERIES A

Aug 2022

$5m

SEED

Total funding: $22.5m

Company HQ

Belterra, TX

Articles

Numbers Station raises $17.5M to bring AI to your data stack

Numbers Station Raises $17.5 Million in Series A

Numbers Station lets business users chat with their data

Leadership

Chris Aberger

(Co-Founder & CEO)

Previously Senior Director of Machine Learning at SambaNova Systems. Prior to that, they were an intern at Google, Apple and IBM.

Ines Chami

(Co-Founder & Chief Scientist)

Before co-founding Numbers Station they were an AI/ML Researcher at Factory. Prior to that, they were a Research Intern at Google and a Data Science Intern at Microsoft.

Sen Wu

(Co-Founder)

Studied at Tsinghua University and Stanford University.

Chris Ré

(Co-Founder)

Also an Associate Professor at Stanford University. Studied Physics and Computer Science at Stanford.

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