Senior Applied ML Researcher
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Design and train deep neural networks for video, image, audio, and audio-visual tasks. Build models for audio-visual representation learning, cross-modal alignment, and fusion. Develop solutions for tasks such as: Video understanding and temporal modeling. Audio-visual event detection. Speech, sound, and scene understanding. Multimodal classification, detection, and localization.
4+ years of experience in deep learning or machine learning engineering\\nstrong expertise in deep neural networks and modern training workflows\\n8 years + Hands-on experience with computer vision and/or audio modeling\\nProficiency in Python and deep learning frameworks (PyTorch preferred)\\nSolid understanding of linear algebra, probability, and optimization\\nAbility to build intuition from problem statement and translate to dataset requirement, neural network design and loss functions
PhD in computer science, machine learning, or a related field, or equivalent practical experience.\\nPublications in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, etc.)\\nExperience with self-supervised or foundation model pre-training\\nOpen-source contributions in vision, audio, or multimodal AI\\nBonus: Experience with Objective-C and/or Swift for on-device deployment
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