BeEmotion.ai
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About
BeEmotion.ai is dedicated to innovating at the intersection of artificial intelligence and human behavior. They provide cutting-edge solutions that enhance interaction, prevent accidents, and bring enjoyment to everyday technology use. They offer market-ready AI solutions including Discovery AI (for research, testing, and product feature discovery), Services (integrating AI into client workflows), and Edge AI (for OEMs). Their AI solutions are applied to Smart Mobility, Smart Living, and Smart Health markets. The company has offices in Australia, Switzerland, and Japan. They are looking to hire an Embedded AI Engineer.
Platform
Task
Features
• services
• edge ai
• discovery ai
• contactless sensing of patient state and vital signs
• real-time human behavior ai solutions
• in-cabin sensing solutions
Job Opportunities
Embedded AI Engineer (senior)
BeEmotion.ai creates AI solutions for enhanced human-machine interaction across Smart Mobility, Living, and Health sectors, offering Discovery AI, Services, and Edge AI solutions.
Benefits:
Competitive salary and benefits package
Opportunity to work on cutting-edge AI projects for edge devices
Work in a collaborative and fast-paced environment
Make a real impact on the development of next-generation AI products
Education Requirements:
Bachelor's degree (master’s degree preferred) in electrical engineering, computer science, or a related field
Experience Requirements:
5 years industry experience
Other Requirements:
Strong understanding of artificial intelligence and machine learning concepts
Experience with developing and implementing AI algorithms, particularly for resource-constrained environments
Experience with embedded systems programming (proficiency in C++ for embedded devices; Python is a strong plus)
Familiarity with various computer hardware architectures (x86 and ARM-based CPUs, GPUs, TPU, NPU, and neuromorphic computing) and resource constraints of embedded systems
Experience with some of the following technologies appreciated: LPDNN, Onnx Runtime, TensorRT, Apache TVM, CMake, ARM Compute Libraries, OpenCV
Working knowledge of Docker for containerization and Git for version control
Excellent problem-solving and analytical skills
Strong communication and collaboration skills
Fluent English. French or German a plus
Responsibilities:
Optimise, deploy and integrate AI models for performance and power consumption on resource-constrained devices
Maintain deployment toolchains for edge devices, managing dependencies, configuration, and automation
Continuously improve runtime and model inference performance on edge devices
Analyse bottlenecks, identify optimization opportunities, and implement solutions to achieve the best possible performance within resource constraints
Develop and execute test plans for AI functionality on embedded systems
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