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 first product, Roboflow Organize, is the key missing infrastructure that allows developers to get raw images into any model framework — replacing a sprawling list of one-off utils everyone has 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 20,000 users working on problems we couldn’t even imagine when we got started!
Today, Roboflow has five full-time members: Amanda, Brad, Jacob, Matt, and Joseph. We also have a high school intern, Jim, who recently finished Calc 3 at the local university. Nikki also recently started part-time – she’s researching our new signups and learning more about how we can best solve their problems. 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 often means building things really quickly and fixing bugs right away.
Various team members enjoy cycling, lake water sports, chess, the outdoors, running, and a smorgasbord of other activities… but we all enjoy learning (especially from one another).
Roboflow went from zero to over 20,000 users in 2020 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.
About the role
What we’re looking for
Roboflow is hiring our second non-founder engineer. As an integral part of our core 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.
The ideal candidate is a “startup person” — we love to hire past and future founders.
What we need from you
You’ll be tasked with a wide range of projects. We’re still small enough that we don’t have the luxury of specialization so we’re looking for a technical generalist that isn’t afraid to dive into a new stack or toolchain if the need arises. Most of the things we work on are parts of the core product but from time to time we’re also working on things like integrating marketing and sales tools, automating internal processes, open source projects, and experimenting with new ML models.
You’ll have a wide degree of freedom to advocate for which projects you think should be highest priority each week and will contribute to our strategy decisions. If you need a rigid list of tasks 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 skillsets 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.
To give you an idea of what it will be like to work here, here are a few projects you might work on:
- Creating a filtering interface so our users can mix and match their images based on metadata like the time of day they were captured, the GPS location, or custom tags they’ve applied.
- Adapting our annotation tool to be embedded as an iframe in end-user applications.
- Working on an on-premise version of Roboflow that we could deploy for enterprise customers.
- Creating a Python package our users can include in their projects to replicate our backend image pre-processing steps in their own code-base so that they’re feeding their machine learning models images formatted the same way as the ones we exported for them to train with.
- Working on a new onboarding flow that walks users through using Roboflow to create a model that detects their company’s logo in images.
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.
To apply for this job please visit www.workatastartup.com.