Infrastructure Engineer at Roboflow (S20)
$120K - $170K  •  0.10% - 0.30%
🖼️ Give your software the sense of sight.
Remote (US)
3+ years
About Roboflow

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.

About the role
Skills: Elasticsearch

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.

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.

The Opportunity

Roboflow is scaling rapidly. We now manage over 100 million images for hundreds of thousands of users. Having secure and reliable cloud infrastructure to support our growth is of paramount importance.

The Roboflow product spans the entire end-to-end machine vision pipeline. So, naturally, the infrastructure presents a wide range of challenges. From driving efficiencies in GPU batch computing to shaving off milliseconds off latencies of our hosted machine learning inference APIs, to supporting hundreds of thousands of users worldwide with best-in-class site reliability and data protection.

Our infrastructure runs across AWS and GCP. Our core web-app runs on Firebase (Firestore, Functions, Storage, Hosting). We heavily utilize serverless compute products where possible, but also run clusters of GPU-powered machines on AWS Batch and in managed instance groups fed by pub-sub queues when necessary. We are increasingly using Kubernetes internally, and are working on a self-hosted version of our platform.

The Role

The focus of this role is on improving, scaling, and maintaining our the infrastructure that powers our core app, including: our cloud architecture, databases, file storage, search cluster, micro-services, and machine learning pipelines.

You'll be working alongside our existing infrastructure team along with doing cross-team work spanning product, operations and customer-facing projects and should have the ability to context switch across a wide range of infrastructure, security and systems engineering work in a fast-paced startup environment.

Specific Skillset

Experience with some or all of the following would be helpful:

  • Infrastructure-as-code - Terraform, bash scripting automation in production environments
  • Site reliability - alerting, monitoring, scaling services in AWS and GCP clouds
  • Node.js and Python programming skills; ability to work with full-stack developers on designing, developing, and operating SaaS applications
  • Experience with running and debugging a self-hosted Elastic cluster in production
  • Experience with machine learning/big data at scale (GPU, Docker and Kubernetes)
  • Awareness of security best practices and tightening infrastructure for highly secure cloud operations; ideally experienced in a ISO 27001 or SoC2 certification for SaaS applications
  • Experience with CI/CD automation (for example Github actions/CircleCI etc.)

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.

Interview Process

We're a tightly knit and highly technical team. As a startup, speed and decisiveness are important; we try to demonstrate that during the hiring process.

  • Application screen
  • Technical screen (via Triplebyte for most engineering roles)
  • Zoom call with hiring manager
  • Zoom call with founder
  • Hacking together on something with the team for a few hours (where applicable)
  • Culture discussion, explanation of benefits, alignment on offer with HR
  • Written offer
  • Offer acceptance
  • On-prem onboarding where practicable

We aim to screen, interview, make a decision, send and finalize an offer within 2 weeks of application.

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