Machine Learning Research Engineer

3–4+ years of hands-on ML research experience; PhD preferred but not required if equivalent industry experience Author on peer-reviewed papers; able to demonstrate track record of meaningful research contributions Expert-level knowledge in PyTorch, modern vision architectures (YOLO, SAM, VLMs), and training pipelines Deep knowledge of object detection, instance segmentation, keypoint detection, SAM, and VLMs

Research and prototype novel computer vision models and training techniques Lead end-to-end ML research projects Help ML Engineers implement and deliver your work Build and iterate on vision models in PyTorch with a focus on segmentation, detection, and few-shot understanding Reproduce and extend results from top academic papers using PyTorch Build open-source and production-quality implementations Work closely with product and engineering Drive innovation in key areas like segmentation, vision-language models, and general-purpose CV models Push the boundaries of what’s possible in vision Maintain high standards for reproducibility, experimentation, and code quality Develop models that outperform existing state-of-the-art tools Contribute to open source and help shape the future of Roboflow’s research direction