Job Informationen

Location: Zug Workload: Full-time Your tasks: Implement state-of-the-art embedded computer vision algorithms for wearable devices, including SLAM, tracking, mapping, scene understanding and AI. Analyze, design, develop, and debug embedded perception stack for a wide variety of AR and VR devices, including novel sensing and imaging systems, haptic devices, and audio prototypes Be a go-to person to escalate the most complex development, performance and evaluation issues that require in-depth knowledge of product-focused firmware development Play a critical role in the definition and execution of long-term roadmaps in partnership with silicon architects, hardware designers, OS team, and algorithm and model development teams Support all phases of hardware development – including early architecture requirements definition for custom silicon, firmware architecture, implementation, simulation, FPGA debug, chip bring up and support systems and software teams on algorithm development on validated systems Collaborate across an interdisciplinary team of researchers and engineers to optimize solutions at the systems level (sensor hardware, data collections, training, evaluation, real-time inference) Design and implement multi-modal models that combine cameras with other sensors, including IMUs and neural interfaces Your profile: Minimum Qualifications: Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. 4+ years’ experience in C/C++ for development, debugging, testing and performance analysis Demonstrated expertise in one or more of the following areas - camera and video pipelines, graphics pipelines, encoding technologies, power management, or prototyping and pre-silicon environments (FPGAs, simulation, emulation) Preferred Qualifications: MSc or PhD in relevant field Experience in low-level / embedded Computer Vision, Machine Learning, Deep Learning or AI. Experience working with embedded hardware platforms and exposure to concepts such as clock-level issues, interrupts, and polling Experience building software for embedded systems or custom SoCs Demonstrated expertise in developing with modern Real Time Operating Systems Experience leading complex features or projects across multiple cross-functional teams

Benötigte Skills

• Hardware
• Support
• Testing
• Video
• Machine Learning
• C
• C++
• Embedded
• Bachelor
• Master