Company Overview
At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that’s critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future.
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Department Overview
We are transitioning from traditional computer vision to an "AI-First" approach, leveraging Foundation Models to solve critical real-world challenges in public safety.
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Job Description
We are seeking a Senior AI Researcher to act as a technical beacon for our AI Engineering organization. In this high-impact role, you will lead the research strategy for Fine-Grained Visual Recognition and Data-Centric AI.
You will not only design State-of-the-Art (SOTA) models but also pioneer the use of Generative AI and Agentic Workflows to revolutionize how we curate, mine, and synthesize training data.
This role requires a balance of deep theoretical knowledge and pragmatic engineering. You will bridge the gap between academic research (CVPR, ICCV, ECCV) and production-grade solutions, driving the development of next-generation capabilities like semantic scene understanding and open-vocabulary search.
Scope of Responsibilities/Expectations:
- 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.