Analytics Data science and IOT Principal
Indexed description
Must have skills:
- Hands-on experience with NVIDIA AI, GPU or edge AI technologies.
- Computer vision, video analytics or sensor-data processing experience.
- Real-time data ingestion and streaming architecture.
- Edge deployment experience across cameras, IoT devices or distributed infrastructure.
- Experience with AI model deployment, testing and optimization.
- Strong technical understanding of synthetic data, simulation or digital twins.
- Practical knowledge of containers, Kubernetes, APIs and cloud/edge integration.
- Ability to support demos, architecture discussions and technical client workshops.
Nice to have skills:
- NVIDIA Metropolis, Deep Stream, Jetson, Omniverse, Cosmos, NIM or NeMo experience.
- Crowd management, smart city, transport, airport, port, campus or public safety experience.
- Kafka, Flink, Spark Streaming or similar real-time data platforms.
- VLMs, physical AI, agentic AI or AI-assisted video understanding.
- Experience creating synthetic data pipelines or scenario libraries.
- Experience with model validation, monitoring, drift detection and performance benchmarking.
- Years of experience: For the stronger technical lead: 7–10+ years
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