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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - Inference Maintainer & Developer Experience - **Company:** Roboflow, Inc. - **Location:** San Francisco, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $155,000.0 - $180,000.0 - **Contract:** Permanent contract - **Skills:** Test Suite, Artificial Intelligence, Computer Vision, Automation of Tests, Computer Programming, Continuous Integration, Machine Learning, OpenCV, Open Source Technology, Tensorflow, Video Editing, Pytorch, Large Language Models, ONNX (Open Neural Network Exchange) Format, Machine Learning Operations, TensorRT, Video Streaming - **Published:** July 17, 2026 - **Apply:** https://www.dice.com/job-detail/56a0153e-0d61-4806-940e-0ef152ed7581 ## About the Role 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 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. ## Description 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 especially.What You'll Do * 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. ## Related Videos - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Deepfakes in Realtime - How Neural Networks Are Changing Our World](https://www.wearedevelopers.com/videos/180-deepfakes-in-realtime-how-neural-networks-are-changing-our-world) - [Robots are coming into the wild! Full-Stack Robotics Engineers, be ready!](https://www.wearedevelopers.com/videos/479-robots-are-coming-into-the-wild-full-stack-robotics-engineers-be-ready) - [Efficient deployment and inference of GPU-accelerated LLMs​](https://www.wearedevelopers.com/videos/929-efficient-deployment-and-inference-of-gpu-accelerated-llms) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)