Machine Learning Engineer - Inference Maintainer & Developer Experience

Roboflow

7d • Hybrid

About The Position

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. At the center of all of this is inference — 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 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. The ideal end state: nightly end-to-end tests across every target (both standalone and on-platform), backed by a growing, world-grounded suite that validates the real health of every build. 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: 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.

Requirements

• 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.

Nice To Haves

• Open source maintenance experience is a strong plus — you know what it takes to steward a busy repo and a community of contributors.

Responsibilities

• Build and maintain inference, 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 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 more effectively.
• Contribute to and grow the broader open source community around the project.

Benefits

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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed