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RADAR Tech Stack
RFID and computer vision platform for autonomous retail operations
RADAR combines RFID hardware and computer vision to automate inventory, checkout, and customer analytics in physical retail stores. The tech stack—Python, Java, Go, C++, FPGA, and LIDAR paired with BigQuery, Kubernetes, and Airflow—reflects a hardware-heavy engineering organization building real-time distributed systems. Active projects span ML infrastructure, RFID hardware development, and CI/CD automation, while pain points cluster around real-time data synchronization across store deployments and scaling ML pipelines—typical signals of a company moving from single-store pilots toward multi-location deployments.
Tech Stack 28 technologies
What RADAR Is Building
◆Challenges
- Real-time data infrastructure in physical stores
- Real-time inventory tracking
- Scaling legal operations
- Lack real-time inventory visibility in stores
- Inventory accuracy challenges
- Store deployment issues
- Operational challenges in retail tech deployment
- Scaling ml pipelines
- Improving reliability and scalability of distributed systems
- Meeting soc 2 compliance
▲Active Projects
- Model performance optimization
- Implementation of radar technology in retail stores
- Rfid hardware solutions development
- End-to-end machine learning pipelines
- Ml infrastructure pipeline
- Feature engineering pipeline optimization
- Rfid inventory management platform
- Designing and maintaining ci/cd pipelines with github actions
- Building infrastructure with terraform
- Optimizing ml ops workflows
Hiring Activity
20 roles · 20 in 30d
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