# Machine Learning Engineer

**Company:** [Roboflow](https://hotfix.jobs/companies/roboflow)
**Location:** New York, NY, San Francisco, CA
**Role:** ML Engineering
**Experience:** 5+ years
**Skills:** PyTorch, TensorFlow, Onnx, TensorRT, vLLM, Opencv, Deepstream, Pillow, Pyav, CI/CD, Computer Vision, Machine Learning
**Posted:** 2026-07-01

> Steward Roboflow's open-source Inference engine by building an agentic-driven contribution, review, CI/CD, and testing pipeline to enable daily releases from high-volume AI-generated PRs while maintaining quality. Own model integration, community enablement, documentation, and customer education for computer vision inference across cloud and edge.

## Job Description

## 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 — 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.

## 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.
- 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.

## Nice-to-Haves
- 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.
- 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.

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