Machine Learning Engineer

Description

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. The company simplifies building and using computer vision models. That includescounting cells (the company's site) to accelerate cancer research, improvingconstruction site safety (the company's site),digitizing floor plans (the company's site),preserving coral reef populations (the company's site),guiding drone flight (the company's site), andmuch more (the company's site).

Our team is small relative to our impact, and we believe our user success is our success (not the inverse). A team member summarized: “the company 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 the company employs developers across the company in design, sales, customer support, marketing, and beyond.

At the center of all of this isinference (the company's site) — one of our most important open source projects and the engine that runs computer vision models everywhere, from cloud GPUs to edge devices in the field. It powers our commercial platform and is relied on by tens of thousands of developers. This role exists to be its steward.

Why This Role Exists

Inference (the company's site) is growing fast — and so is the volume of contributions, increasingly authored with the help of AI agents. That's a great problem to have, but it's outpacing our ability to keep quality high and cut releases on a predictable cadence. Today we ship roughly weekly, and it's a fight.

We want to flip that equation. The goal is to build and continuously evolve an agentic-driven contribution and release pipeline — automated and semi-automated review, triage, CI/CD, and end-to-end testing — so that we can safely absorb a high volume of agent-generated PRs while staying firmly in control of quality. With that foundation, daily releases become routine, and we can say "yes" to far more contributions without ever lowering the bar — pushing back, by design, according to strictly defined review standards.

Alongside that, this person becomes the human face of inference (the company's site): teaching internal teams and customers how to get more out of it, partnering with marketing to tell its story, and owning the (genuinely fun) work of bringing new models into the engine.

Responsibilities

• Build and maintain inference (the company's site), our flagship open source and commercial CV inference engine, keeping it healthy and high-quality as contribution volume scales.
• Build an agentic-driven contribution pipeline — automated and semi-automated review, triage, and CI/CD — so we can safely accept a high volume of agent-generated PRs and move from weekly releases toward daily ones.
• Design and grow a world-grounded, ever-expanding test suite that validates real build health across every target (standalone and on-platform), with the goal of nightly end-to-end runs across all of them.
• Define and enforce the "rules of the road" — the review standards and skills that agents and contributors must follow. Exercise sharp judgment on when to merge fast and when to push back, and encode that judgment into the system itself.
• Streamline how new models get added to inference (the company's site) (the most fun part of the job) — making it dramatically faster and easier to bring the latest computer vision and ML models to our users.
• Teach and enable internal teams and customers. Keep our Field Engineers and Support team a step ahead so they can self-serve and go deeper, and help customers get the full value of the product.
• Be the bridge between core engineering and clients — translating new capabilities into docs, demos, stories, and launches which would help people use inference (the company's site) more effectively.
• Contribute to and grow the broader open source community around the project.

Requirements

• Primarily, you like to make great things with passionate colleagues. You are someone who 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 who thrive in the level of autonomy at the company. Maybe you had a side hustle in high school or college.
• You care about open source and the developers who depend on it. One of the best ways to stand out among other applicants is to write about something you've built with the company, or to contribute to one of our open source projects — inference (the company's site) especially.
• You are an experienced Machine Learning practitioner who wants to be an important part of an exceptional team that focuses on using the company'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.
• A real CV/ML foundation — you understand what inference does: how computer vision models work internally, how they're deployed across diverse environments, and how to adapt them for real-world, high-impact use.
• Stellar agentic skills. You build with AI coding agents fluently and have a track record of using them not just to ship features, but to automate the engineering process itself — review, triage, testing, and CI. You have strong instincts for where agents excel and where they need guardrails.
• Strong CS and systems background , with the ability to independently tackle complex programming, architecture, and reliability challenges and exercise sound judgment on when to move fast and when rigor is essential.
• Hands-on experience with CI/CD, release engineering, and test infrastructure — you've built or substantially improved automated testing and delivery pipelines before.
• Practical expertise with core ML technologies , including several of the following: PyTorch, TensorFlow, ONNX, TensorRT, vLLM (or other LLM/model deployment tools).
• Strong proficiency in image and video processing , including several of the following: OpenCV, DeepStream, Pillow, PyAV, hardware-accelerated video decoding. Experience with video streaming protocols is an advantage.
• Excellent communication and soft skills. You can teach, write clearly, and collaborate across engineering, support, field, and marketing — and you actually enjoy it. You're comfortable being a public-facing voice for a project.
• Open source maintenance experience is a strong plus — you know what it takes to steward a busy repo and a community of contributors.
• Level-up your performance with AI agents.
• Where You'll Work
• The company 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 (the company's site) (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. This role has a range of $155K - $180K depending on level and location of candidate. We are open to paying beyond these ranges for exceptional talent. If this is you, please apply
• 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
• $350/mo AI Tools stipend
• Cover up to 100% of your health insurance costs for you and your partner or family
• $150/mo team lunch stipend
• 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
• 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 the company or contribute to one of our open source projects (the company's site).
• We may send you a technical screen if applicable.
• Introduction Phase:
• [15m] Technical Assessment
• Team Interview Phase:
• Live coding [45m]
• Home assignment
• [30m] Meet with Inference Core team member
• [60m] Meet with hiring manager
• Final Interview Stage:
• [45m] Meet with Head of Operations for a culture discussion
• [30m] Meet with 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 removed]](mailto:[email removed]) or subscribe to our career newsletter by emailing "Subscribe" to [[email removed]](mailto:[email removed]). 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
• Experience: Any (new grads ok)
• Visa: US citizen/visa only