Motorola Solutions

Tóm tắt công việc

• Advanced Model Research: Lead the R&D of high-performance models for Fine-Grained Visual Categorization (FGVC) and Hierarchical Classification, focusing on detecting complex object attributes and nuances in unconstrained environments using both Supervised and Self-Supervised Learning (SSL).
• Generative AI & VLM: Spearhead the exploration of Vision Language Models (VLM) and CLIP-based architectures to enable Text-to-Image / Image-to-Image retrieval and Open-Set Recognition, moving beyond fixed-class taxonomy.
• Agentic Data Workflows: Architect and implement AI Agentic Workflows to automate the data lifecycle. Design intelligent agents for autonomous data mining, auto-captioning, and Synthetic Data Generation to overcome long-tail edge cases and reduce reliance on manual annotation.
• Production-Grade AI: Drive the transition of models from research prototypes to production. Collaborate with Embedded AI Engineers to guide the distillation and quantization of heavy Foundation Models for deployment on edge devices.

• Deep Learning Mastery: Expert-level understanding of Deep Learning architectures, specifically Transformers (ViT, Swin), CNNs (EfficientNet, ResNet), and Object Detection/Segmentation frameworks.
• Generative AI & Multi-modal: Hands-on experience with Multimodal Foundation Models (CLIP, LLaVA, etc.) and Generative approaches (Diffusion Models, GANs) for data synthesis.
• Data-Centric AI: Proven track record in building automated data pipelines. Experience with Active Learning, Auto-labeling, or building "Agentic" systems for data curation is a critical differentiator.
• Frameworks: Proficiency in PyTorch (preferred) or TensorFlow, and strong programming skills in Python and C++.
• Practical Implementation: Strong ability to write clean, maintainable code and experience with MLOps practices (CI/CD for ML, Experiment Tracking).
• Education: Bachelor’s Degree or higher in Computer Science, Artificial Intelligence, Computer Vision, Mathematics, or a related technical field.
• 7+ years of relevant industry experience in Computer Vision and Machine Learning.
• Proven track record of leading technical initiatives and successfully deploying AI models into commercial products (0-to-1 product lifecycle experience is highly preferred).
• Demonstrated ability to lead and mentor technical teams in a fast-paced R&D environment.