Principal Software Engineer, Voxel51

$225-260k

+ Stock Options

MongoDB
Python
Elasticsearch
Tensorflow
NumPy
PyTorch
Slack
Senior and Expert level
Remote in Canada, US

More information about location

Voxel51

Data platform for computer vision models

Open for applications

Voxel51

Data platform for computer vision models

21-100 employees

B2BData storageComputer VisionSaaSData Analysis

Open for applications

$225-260k

+ Stock Options

MongoDB
Python
Elasticsearch
Tensorflow
NumPy
PyTorch
Slack
Senior and Expert level
Remote in Canada, US

More information about location

21-100 employees

B2BData storageComputer VisionSaaSData Analysis

Company mission

Voxel51's mission is to bring transparency and clarity to the world's data through its computer vision data modelling platform.

Role

Who you are

  • 8+ years of professional software engineering experience developing flexible and scalable APIs and software architectures
  • BS or MS in computer science or a related field
  • Proficiency with Python
  • Expertise with NoSQL databases (MongoDB, DocumentDB, Elasticsearch)
  • Familiarity with machine learning and scientific computing libraries (TensorFlow, PyTorch, NumPy)
  • Experience maintaining or contributing to open source projects (or the passion to start!)
  • Ability to work in a remote-first, cooperative environment using collaborative development tools (GitHub, Slack)

What the job involves

  • As a software engineer at Voxel51, you’ll collaborate with a team that delivers features to support dataset curation, model analysis, and integrations that span the entire machine learning lifecycle
  • You’ll build clean, scalable APIs and solve unique challenges that arise when working with unstructured data (images and video)
  • You’ll have the opportunity to contribute to a thriving open source community while also emphasizing enterprise-grade engineering for our commercial products
  • Design and develop open source and enterprise APIs and backend systems
  • Lead, mentor, design, and deliver
  • Build data models that scale from individual users to Fortune 500 companies; processing petabytes of data

Otta's take

Sam Franklin headshot

Sam Franklin

CEO of Otta

Recent innovations in computer vision mean that AI can recognise images within large-scale datasets, presenting significant opportunities for innovation in just about every industry. However, this only works successfully when AI is trained with high-quality datasets, and it is difficult to organize, locate, and correct mistakes at such high scale.

Voxel51 provides a data platform for computer vision models called FiftyOne, an open-source toolkit that helps users automate the organization, navigation, and creation of computer vision models, regardless of size. The platform also includes automated data quality control tools to help users identify detrimental mistakes within models, a process that is necessary for successful computer vision.

Many startups are tackling inefficient computer vision workflows, but Voxel51 has found a gap in the market by focusing specifically on the laborious manual processes associated with organizing and aggregating high-quality datasets. It has formed a collaborative partnership with Google, empowering its platform with Google's pre-annotated image datasets, and recently announced an AI assistant that can generate Python Code for computer vision dataset analysis.

Insights

Top investors

Few candidates hear
back within 2 weeks

Company

Funding (last 2 of 4 rounds)

May 2024

$30m

SERIES B

Sep 2022

$12.5m

SERIES A

Total funding: $45.8m

Company benefits

  • Medical, Dental & Vision
  • Flexible work schedules
  • Generous PTO
  • Family-friendly policies
  • Stock options
  • 401k matching
  • Flexible set-up
  • Rich team building
  • Healthy remote playbook

Company HQ

Ann Arbor, MI

Founders

Jason Corso

(Chief Science Officer)

Experience as Director of the Stevens Institute for Artificial Intelligence. Associate Professor of Electrical Engineering and Computer Science at the University of Michigan since 2014.

Was a Software Engineering and Research Intern at Google. Also a Graduate Research Assistant at the University of Michigan from 2012 to 2017.

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