Description
Design, train and improve computer vision and VLM models for object understanding andrecognition.Make models robust to real-world conditions and across devices and fix failure modes on realdataDefine evaluations that reflect product quality, and use them to drive model decisions.Design models for on-device constraints (memory, latency, power).
Minimum Qualifications
Ph.D. or Master's in Computer Science, Machine Learning, Computer Vision or a related field,or equivalent industry experience.Strong foundations in computer vision and deep learning.Track record of making models work in practice: end-to-end projects covering data, trainingand evaluation on real-world visual data.Proficiency in Python and PyTorch or an equivalent deep learning framework.Proficiency in using generative coding toolsRigorous experimentation: clear baselines, ablations and meaningful evaluation sets.
Preferred Qualifications
Publications in top computer vision or machine learning venues (CVPR, ICCV, ECCV,NeurIPS, ICLR), ideally with released code or work transferred to a product.Experience in representation learning, such as self-supervised learning, metric learning,retrieval or recognition.Experience applying machine learning in an industry or product setting.Experience with knowledge distillation or model compression.Familiarity with vision-language models.
Learn more about this Employer on their Career Site
