Applied Machine Learning Research Engineer at Roboflow

Key Skills

Aartificial intelligence, AWS, Computer Vision (CV), Docker, Google Cloud Platform (GCP), Machine learning techniques, macOS platform, Python Programming, PyTorch, TensorRT

Job Description

What We're Looking For

Primarily, you like to make great things with passionate colleagues. You are someone that likes to own outcomes, not only inputs. You’re motivated by having responsibility and accountability. You’re eager to ‘do the work,’ big and small.

You’re curious and learning about new technologies, perhaps an early tinkerer with ChatGPT and AI products. You show more than you tell.

You’re motivated by the question, “How can I improve this?” and have a track record of doing so, even in ways adjacent to your role. Much of our current team is made up of former founders and thrive in the level of autonomy at Roboflow. Maybe you had a side hustle in high school or college.

Many Roboflowers have used our tools before joining. One of the best ways to stand out amongst other applicants is to write about something you have built with Roboflow or contribute to one of our open source projects.

What You'll Do

Roboflow is hiring our first research engineer on the machine learning team to drive research initiatives that improve the growing suite of machine learning tools that underpin the Roboflow application. Roboflow is actively used by thousands of engineers and it is now imperative for us to keep our machine learning tooling at the cutting edge and to push the state of the art forward in the ways that we are uniquely positioned, given the breadth of computer vision applications that our product is capturing.

This role will involve adapting and extending open source machine learning technologies into usable and scalable software. Wide-ranging curiosity and enthusiasm for diving into abstract problems, coming up with good solutions, and seeing them through to completion are essential responsibilities.

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.

 Within one week, you will…

• Learn all about computer vision, our product, company, customers, and vision.

• Ship something substantial to an end user

 Within one month, you will…

• Onboard in person with your manager (you’ll come to our NY or SF Hub!)

• Build your first computer vision project with Roboflow (if you haven't already)

 Within six months, you will…

• Attend your first all company onsite

• Be ramped up on other relevant parts of the Roboflow product.

Who You Are

You are a curious self-starter who wants to be part of an exceptional team, with a focus on using Roboflow's computer vision tools to impact and improve every industry.

On the machine learning team, we primarily work on building and maintaining technology within Roboflow’s training, search and deployment services, but from time to time we're also helping deliver on enterprise contracts, and coding awesome open source projects and sample projects. We currently support the fine-tuning and deployment of object detection, classification, instance segmentation, and semantic segmentation models. In the beginning, you will be executing on research initiatives that we have embarked on with partner organizations - centered around the Roboflow 100 object detection benchmark. As we discover results within these initial projects, the role will branch into your own curiosities in the intersection of computer vision research, AI research, and the Roboflow application. If you need a rigid list of tasks spelled out in a multi-month roadmap, this role probably will not be a good fit.

We’re especially keen to add someone to our team who has deep experience and passion in the field and will help us live on the frontier of computer vision technology.

Skills - you should be familiar with many of these concepts and technologies and have built projects with some of them:

• Machine Learning Research: PyTorch, ONNX, TensorRT, TFjs, YOLO, Transformers, COCO

• Backend + Cloud: node, Docker, python, Flask, pip, REST, AWS, GCP

We anticipate the role being focused 50% on machine learning research and 50% on implementing results of your research into the Roboflow application. You certainly don't need to be an expert 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. Your opinions on which research ideas we tackle and how we integrate them will be highly valued.

Example Projects

• Extending the capabilities of the Roboflow 100 auto-benchmark server

• Training a YOLOv8 Objects 365 checkpoint on YOLOv8 and evaluating how much it improves Roboflow 100 training results

• Writing a blog and example training notebook on DETA

• Assessing and implementing an auto-batching strategy for our training machines

• Surveying general open source OCR models and implementing one of them in the Roboflow inference server

• Assessing and implementing Neural Magic apis to deploy Roboflow models

• Training a general object detector across on Roboflow Universe datasets

• Evaluating capabilities of zero-shot object detection models for label assist

Who You'll Be Working With

Our team of ~50 attracts talent like executives that wanted to return to building, founders with a 100M+ exit, Roboflow users turned team members, open source contributors, a cyclist who biked across the United States, prolific high school hackers, a CTO from 100+ engineering organization, amongst many exceptional others.

You will directly be working with our Machine Learning Lead and a team of Machine Learning Engineers.

Where You'll Work

Roboflow is distributed across the US and Europe. We currently have Hubs in New York City and San Francisco (and plan to open more as we grow density in new cities). We provide opportunities (like team onsites in different cities) and resources (like a $4000/yr travel stipend) to work in person with other team members as much as you'd like, while also supporting remote team members. You can work from one of our Hubs (we offer a relocation bonus), work from home, work at co-working spaces, etc. We want you to work where you work best!

When You'll Work

Roboflow primarily operates during the daytime hours in the US and there are some synchronous meetings you’ll be expected to attend each week. Apart from that, we have a flexible schedule that allows you to work collaboratively with other team members and asynchronously when needed.

What You'll Receive

To determine your salary, we use a number of market and data-driven salary sources. We review all salaries every six months to ensure we stay in line with the market.

 The target compensation for this role is $180,000 base.

 In addition to our cash compensation, we offer generous perks and benefits. Below are some of the highlights:

• $4000/yr Travel Stipend to travel anywhere anytime to work alongside other Roboflowers

• $350/mo Productivity stipend to spend on things that make your work environment more productive, like high-speed internet at home or a co-working space

• Cover up to 100% of your health insurance costs for you and your partner or family

• Equity in the company so we are all invested in the future of computer vision

Interview Process (~5 hours)

Below is the interview process you can expect for this role. We are all motivated to work with an exceptional team and don't currently have in-house recruiters. You will be speaking directly with our team about what it's like to work and thrive at Roboflow. We like to be decisive and work fast, so don't be surprised if all the below conversations happen over a day or two.

Before the Interview:

• We’ll review your application, LinkedIn, Github, etc.

• The best way to stand out is to write about something you’ve built with Roboflow or contribute to one of our open source projects.

• We may send you a technical screen if applicable.

Introduction Phase:

• [45m] Meet with hiring manager, Machine Learning Lead, for introduction to assess for overall mindset and skillset

• This first interview is a time to get to know more about the role, allow us to get to know you better, and ensure it's a good fit for both parties to continue moving forward in the process

• [45m] Technical Assessment, if applicable

Team Interview Phase:

• [30m] Meet with CTO, Brad Dwyer

• [60m] Meet with hiring manager again

• Use this time to review specifics about the job description

• Begin working through your 30/60/90 projects

• Ask questions!

Final Interview Stage:

• [30m] Meet with Kate Wagner, Head of Operations for a culture discussion

• [60m] Meet with Joseph Nelson, CEO

• We check references and conduct a background check

Note: you are welcome to request additional conversations with anyone you would like to meet and we will accommodate as best we can.

Technology

Our goal is to build the world's best computer vision paradigm and corresponding code infrastructure to back our customer’s applications. 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.

Our machine learning infrastructure runs in AWS, with a few deployments spanning into GCP. We train and deploy various state of the art models in a variety of machine learning frameworks. All of our machine learning applications are closely integrated with the core Roboflow web application.