Embedded Computer Vision Engineer

About Ultralytics:

At Ultralytics https://ultralytics.com/, we commit to relentless innovation in the AI space and seek team members https://www.ultralytics.com/about who resonate with our ambition to produce the world's best YOLO AI models https://ultralytics.com/yolo. If you're obsessed with AI, eager to make an impact on the world, and thrive in dynamic, high-intensity environments, we invite you to apply for a position on our team.

🌍 Join the team powering the future of vision AI Hello, hola, 你好, こんにちは, नमस्ते, hallo, bonjour! Thanks for stopping by — we know your time is valuable, so here's what makes Ultralytics special.

⚡ Who we are At Ultralytics https://www.ultralytics.com/, we're on a mission to simplify AI for everyone. As the creators of the world's leading Ultralytics YOLO models https://docs.ultralytics.com/models/, we empower millions of developers, researchers, and companies worldwide to build state-of-the-art computer vision applications with our open-source tools https://github.com/ultralytics.

Following our $30M Series A round https://www.ultralytics.com/news/ultralytics-raises-30m-series-a, we're expanding rapidly across our global hubs in London, Madrid, and Shenzhen. This is an opportunity to join a fast-scaling, high-performance team that's redefining the future of vision AI — where ambition meets impact, and ideas become reality.

We move fast. We build boldly. We execute with purpose. And we do it together.

💼 About the role As Embedded Computer Vision Engineer, you'll take YOLO models from PyTorch to production on edge hardware. You'll build and maintain export and inference integrations in the Ultralytics package https://github.com/ultralytics/ultralytics, helping models run accurately and efficiently across CPU, GPU, NPU, and SoC platforms.

You'll own technical integrations with silicon and hardware partners, translating between model requirements and platform constraints. Working across export formats, inference runtimes, and real devices, you'll ensure partners and their customers can deploy YOLO with confidence.

This senior role suits an engineer with strong ML fundamentals, hands-on edge hardware experience, and the communication skills to work directly with internal teams and external partners.

🚀 What you'll do Export & runtime integration

• Build and maintain export https://docs.ultralytics.com/modes/export/ and inference integrations, from model conversion to on-device support.

• Keep integrations working across Python, PyTorch, and vendor SDK releases.

• Review partner contributions and validate integrations on real hardware before release.

Deployment, benchmarking & accuracy

• Set up embedded boards and development kits for YOLO deployment and testing.

• Optimize models for target hardware, balancing latency, memory, and accuracy.

• Debug accuracy loss caused by conversion and INT8 quantization.

• Benchmark and profile YOLO tasks https://docs.ultralytics.com/tasks/ and model generations, publishing results in the documentation https://docs.ultralytics.com/.

Partner integrations

• Own technical relationships with hardware and silicon partners, including active AMD work and integrations with Google and Nvidia platforms.

• Lead partner engineering syncs and define clear integration guidelines.

• Translate platform constraints into model, runtime, and deployment requirements.

• Work with partner compiler teams to support new YOLO architectures at launch.

Infrastructure, documentation & support

• Diagnose issues across models, runtimes, drivers, and devices with ML engineers and partner teams.

• Maintain hardware CI on self-hosted and partner-hosted devices, plus deployment Docker images.

• Write integration guides https://docs.ultralytics.com/guides/ and device benchmark pages.

• Create developer content, live sessions, and demos for industry events.

• Support developers and customers through GitHub https://github.com/ultralytics, the community forum https://community.ultralytics.com/, and our sales team.

🧠 Skills and experience Core requirements

• Strong foundation in machine learning or computer vision, including how YOLO models work.

• Strong Python skills and working experience with PyTorch and ONNX.

• Hands-on experience with TensorRT, OpenVINO, ONNX Runtime, or a vendor NPU SDK.

• Experience with INT8 quantization, calibration, and debugging accuracy loss after conversion.

• Hands-on edge device experience with NVIDIA Jetson, Raspberry Pi, or NPU development boards.

• Experience flashing, configuring, and debugging deployments on constrained hardware.

• Comfortable with Linux, Docker, and Python dependency management across platforms.

• Strong software engineering practices, including clean code, Git pull requests, and code review.

• Clear written English for documentation and communication with internal and external teams.

• Senior-level experience owning technical integrations end to end with minimal oversight.

• Passion for AI, computer vision, and practical, high-impact engineering.

Nice to have

• Direct experience working with silicon vendors or hardware partners.

• Experience across multiple embedded and edge ecosystems.

• C++ experience, including model deployment on microcontrollers.

• Experience running CI on self-hosted hardware runners.

• Contributions to open-source projects or developer ecosystems.

• Experience collaborating across international teams.

• Willingness to travel to industry events.

🌟 Cultural fit At Ultralytics, we set bold goals and execute with speed, precision, and teamwork. We're driven by hard work, ambition, and resilience — building fast, learning constantly, and delivering measurable impact.

You'll thrive here if you:

• Take ownership and deliver results with focus and accountability.

• Combine strategic thinking with hands-on execution.

• Value excellence, grit, and creativity in equal measure.

• See collaboration as the foundation for meaningful progress.