Machine Learning Engineer - Deployments Team

Machine Learning Engineer - Deployments Team

Who We Are

Our mission is to make the world programmable. Sight is one of the key ways we understand the world, and soon this will be true for the software we use, too.

We’re building the tools, community, and resources needed to make the world programmable with artificial intelligence. Roboflow simplifies building and using computer vision models. Today, over 1M+ developers, including those from half the Fortune 100, use Roboflow’s machine learning open source and hosted tools. That includes counting cells to accelerate cancer research, improving construction site safety, digitizing floor plans, preserving coral reef populations, guiding drone flight, and much more.

Our team is small relative to our impact, and we believe our user success is our success (not the inverse). A team member summarized: “Roboflow is a company full of giant brains and tiny egos.” We find software has a multiplier effect on all roles (not only product and engineering), so Roboflow employs developers across the company in design, sales, customer support, marketing, and beyond.

We’re supported by great customers and investors, having raised over 63 million from Google Ventures, Y Combinator, Craft Ventures, Sam Altman, Lachy Groom, amongst other leading software investors.

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 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

• Design and deliver advanced solutions that generate predictions from a wide range of Computer Vision models across diverse deployment environments — from cloud infrastructure to distributed edge devices.

• Build and evolve key components of the Roboflow Platform to ensure seamless, reliable model deployment at scale.

• Experiment with cutting-edge models and deployment technologies to identify optimal approaches and push the boundaries of performance.

• Optimize existing systems to improve speed, reliability, and overall efficiency.

• Collaborate closely with cross-functional Roboflow teams to provide tooling and deployment solutions that empower internal teams and enhance customer experience.

• Maintain and improve current deployment pipelines and infrastructure to ensure long-term stability.

• Contribute to and maintain Roboflow’s open-source projects, helping grow and support the broader developer community.

Who You Are

You are an experienced Machine Learning practitioner who wants to be an important part of an exceptional team that focuses on using Roboflow's computer vision tools to impact and improve every industry. You have high agency and a bias toward action.

• 5+ years of hands-on experience building and operating production-grade ML systems, ideally involving large-scale deployment of modern AI models.

• Practical expertise with core ML technologies, including several of the following: PyTorch, TensorFlow, ONNX, TensorRT

• Strong proficiency in image and video processing, including several of the following: OpenCV, DeepStream, Pillow, PyAV. Experience with video streaming protocols will be considered an advantage.

• Strong foundational understanding of ML models, including how they work internally and how to adapt them for real-world, high-impact applications.

• Solid Computer Science background, with the ability to tackle complex programming and architecture challenges.

• Strong system design skills, with experience designing scalable and reliable systems.

• Ability to independently deliver high-quality solutions, exercising sound judgment on when to move fast and when engineering rigor is essential.

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!

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 $163,000 - $182,500 base depending on level and experience. We use Tier 1 rates for employees who work out of our San Francisco & New York hubs more than 3+ times per week.

📈 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

• Remote first/flexible schedule allowing you to work collaboratively with other team members and asynchronously

• Unlimited PTO- with an annual 2 week minimum, we encourage you to take time off for yourself

• 12 weeks parental leave

• 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.

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:

• [30m] Meet with hiring manager to assess for overall mindset and skillset

• [30m] Technical Assessment

  • Technical discussion about candidate’s experience

Team Interview Phase:

• Live coding [45m]

• Home assignment

• System-design whiteboard session [30m]

• [30m] Meet with another member of the Deployments Team - Machine Learning Engineer

• [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:

• [45m] Meet with Kate Wagner, Head of Operations for a culture discussion

• [30m] Meet with Joseph Nelson, CEO

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

Not sure if this is you?

We want a diverse, global team with a broad range of experience and perspectives. If this job sounds great, but you’re not sure if you qualify, we encourage you to reach out to us at [email protected] or subscribe to our career newsletter by emailing "Subscribe" to [email protected]. We carefully consider every application and will either move forward with you, find another team that might be a better fit, keep in touch for future opportunities, or thank you for your time.

Learn More About Us

At Roboflow, we believe great ideas come from everywhere—and everyone. We’re proud to be an Equal Opportunity Employer committed to building a diverse and inclusive team. We consider all qualified applicants regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, veteran status, or any other legally protected characteristics.

30-60-90 Plan

A successful candidate would be expected to:

1. Within first week, complete their first-week-ship as small contribution to Inference - bug-fix or small feature

2. Within first two weeks, complete their Visionary Project

3. Within first 30 days:

   • Lead one inference deployment release cycle (hold everyone accountable to merge PRs, coordinate and review them, execute tests, deploy the infrastructure, cut the release)

   • Solve one technically challenging problem in scope of existing team’s duties

   • Identify the areas of the team’s roadmap that the candidate will step into as a person leading the effort

   • Launch at least 1 new PR to production each week

4. Within first 60 days:

   • Candidate solves at least one major problem for an existing customer

   • Candidate leads a medium-size initiative as the directly responsible individual.

   • Collaborate cross-team to find early-adopter customers for the solution they’re leading

   • Ramp up in business & customer context

   • Start being a person that other team members are asking questions about at least one component of the deployment services stack

5. Within first 90 days:

   • Complete the team initiative that they were responsible for and drive adoption and iteration

   • Lead one new initiative which is mission-critical for the team’s success

   • Become an expert in answering questions about Roboflow deployment stack

   • Fully ramped up & participate in quarterly planning