We're on a mission to remove barriers that prevent developers from building their own computer vision applications. Roboflow streamlines the process of labeling, training, and deploying a computer vision model.
Computer vision is going to transform every industry. We're already seeing this play out in fields like transportation (self driving cars), agriculture (drone spraying), and medicine (early stage cancer detection). But these superpowers shouldn't be locked up in the handful of giant technology companies that can afford to hire teams of machine learning PhDs.
Roboflow enables any developer to use computer vision without being a machine learning expert. Our product is the key missing infrastructure that allows developers turn raw images into a useful model -- replacing a sprawling list of one-off utils everyone previously had to reinvent and enabling our users to have working models in hours, not weeks.
For example, Sarah Hinkley from Barn Owl Drones uses vision to identify weeds from crops in drone images so her customers can use fewer herbicides and grow more. She's one of our over 50,000 users working on problems we couldn't even imagine when we got started!
Today, Roboflow has eight full-time team members spread across the United States. Their roles range from machine learning to sales. We also have a high school software development intern, and a part-time employee researching our new signups. Kelo, Amanda's dog, is the best at frisbee among us.
We're united in our common goals to create high quality products and place our users first. Since we're a small upstart, that means building things really quickly and fixing bugs right away. As with any rapidly scaling startup, we hope to build a team that is both versatile and adaptable. This role has tremendous potential for growth. As such, we believe that coachability and enthusiasm are more important than experience or qualifications. If you’re excited about this opportunity, we want to hear from you.
We strongly encourage applicants from backgrounds that are traditionally under-represented in tech to apply - especially those who identify as Black, Latinx, Native American, Asian and/or LGBTQ+. People who identify as part of these groups have also been under-represented at Roboflow, but intentionally recruiting a team with unique backgrounds is one of several ways we are working to add more distinct viewpoints to our company.
Roboflow went from zero to over 20,000 users in 2020 (and now to over 50,000 in 2021) and our customers are requesting features and product enhancements faster than we can provide them.
We're starting to build out our engineering, marketing, and sales teams. As an integral part of our core team, all roles will inevitably involve wearing a lot of hats; we're specifically looking for people excited about learning new things and filling gaps where needed. And most importantly, we're looking for people who ship.
Check out our Careers page for more info on the company, how we work together, and how we're building strong culture and camaraderie in a post-COVID world.
Roboflow is rapidly expanding our engineering team to address the groundswell of user and customer needs. Over 100,000 developers (spanning from students to individual hackers & hobbyists to startups to employees of some of the world’s biggest companies) have now used Roboflow to build computer vision projects. Soon, every developer will have computer vision as a tool in their toolbox. Roboflow will be for computer vision what Microsoft was for the PC and Google was for the Internet.
We’re looking for strong technical generalists to contribute to our core product and help us build the foundation for our rapidly expanding company.
As an integral part of our early team, this role will inevitably involve wearing a lot of hats. Wide-ranging curiosity and enthusiasm for diving into abstract problems, coming up with good solutions, and seeing them through to completion is essential.
Our core belief is that computer vision is a foundational technology that is going to transform nearly every industry. This is an opportunity to shape how millions of developers will experience and use it for the first time. Your contribution will have a massive impact.
Most of the things we work on are parts of the core product (which is an end-to-end pipeline for building computer vision projects spanning from image ingestion to annotation to training and deployment) but from time to time we're also working on things like integrating marketing and sales tools, fighting fires, automating internal processes, and open source projects.
You'll have a wide degree of freedom to advocate for which projects you think should be highest priority and will contribute to our strategy decisions. If you need a rigid list of tasks spelled out in a multi-month roadmap, this role probably won't be a good fit.
You certainly don't need to be experienced in all of these areas; but should be excited to learn new skill sets as you need them. We also hope you'll bring some new knowledge and experiences you can share to help level-up the rest of the team.
We’re especially keen to add some rigor to our processes and build the foundation for rapidly scaling the engineering organization (for example: we currently have limited tests and are not using an opinionated front-end framework -- things that will need to change over the coming months in order to be able to seamlessly expand the team).
To give you an idea of what it will be like to work here, here are a few projects you might work on in your first few months:
Our goal is to build the world's best computer vision infrastructure so our users don't have to. This means we handle a lot of challenging complexities like seamlessly ingesting dozens of data formats, processing millions of images per day, and deploying auto-scaling machine learning infrastructure that can handle our customers' most demanding training and deployment needs.
Our core app sits atop Firebase with assistance from auto-scaling groups of Docker containers (for jobs like archiving datasets and training models). We also heavily lean on serverless infrastructure so we can gracefully deal with bursty traffic involved in manipulating datasets that can range anywhere from one hundred to one million images.
We also maintain a library of Colab notebooks our customers can use to train common computer vision models, a directory of public datasets, and a web of format specifications. We see building and supporting mini-projects like these that are helpful to the community at large as part of our role in democratizing computer vision.