The AI Infrastructure team at Zensors builds the engine that powers our visual sensing platform. We provide the tools to automate the lifecycle of our AI workflow, including model development, evaluation, optimization, deployment, and monitoring across thousands of video streams. As a Machine Learning Engineer in ML Runtime & Optimization , you will develop technologies to accelerate the training and inference of computer vision models that power smart spaces and cities. Your responsibilities will include: Optimizing Core ML Pipelines: Identifying key bottlenecks in our current video analytics pipeline and performing in-depth analysis to ensure the best possible performance on current server and edge compute architectures. Cross-Stack Collaboration: Collaborating closely with AI research and platform engineering teams to optimize core parallel algorithms and influence the design of our next-generation inference infrastructure. Model Acceleration: Applying advanced model optimization techniques—such as quantization (Int8/FP16), pruning, and layer fusion—to our Vision Transformers (ViTs) and CNNs to maximize throughput and minimize latency. Building Efficient Operators: Working a
Pro unlocks apply links & auto-apply
Spam, scam, fake employer, broken apply link — let us know and we’ll review within 24h.
Report this listing