Machine Learning Engineer - Inference Maintainer & Developer Experience

Roboflow, NY, SF or Remote

The role

At the center of all of this is inference https://github.com/roboflow/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.

What you will do

Build and maintain inference https://github.com/roboflow/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.

What you need

What we're looking for

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 Roboflow. 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 Roboflow, or to contribute to one of our open source projects — inference https://github.com/roboflow/inference especially.

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.
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.

Machine Learning Engineer - Inference Maintainer & Developer Experience

The role

What you will do

Machine Learning Engineer - Inference Maintainer & Developer Experience

The role

What you will do

What you need

What we're looking for

Who you are

Why this role exists

Where you'll work

What you'll receive

Interview process (~5 hours)

Before the Interview

Introduction Phase

Team Interview Phase

Final Interview Stage

About Roboflow

Roboflow