Top Tech Jobs & Startup Jobs

Design, train, optimize, and validate deep learning and computer vision algorithms for edge devices. Implement and optimize models for runtime on Ambarella hardware and assess performance on large-scale datasets.

Test and validate optical and image-processing performance of cameras and sensors. Design and run multi-scenario test cases (indoor/outdoor), debug image quality with developers, evaluate results, produce test reports, and support product optimization, demos, and exhibition activities.

Develop, bring up, and verify embedded platforms and drivers in C/C++ on ARM/MIPS. Work with RT-Linux, lab equipment, and hardware teams to implement and test low-level control drivers and ensure system-level integration.

Develop, tune, and debug digital image/video processing software for cameras (Digital/Hybrid/IP/DV camcorders). Focus on image/video color and quality tuning, software debugging on PC, and cross‑team collaboration.

Design and verify video-compression, image-processing, vector-compute, and edge AI processor subsystems using SystemVerilog/Verilog. Synthesize and optimize RTL for timing, area, and power; prototype microarchitectures with scripting; develop unit tests, front-end flows, and coverage analysis; participate in chip bring-up and testing.

Install, maintain, and troubleshoot Linux servers and core infrastructure services (Kickstart, DNS, DHCP, NFS, LDAP, NIS). Administer Apache, manage container environments (Docker/Podman), implement security and patching, create documentation and runbooks, perform root cause analysis, and provide helpdesk-level technical support.

Work on computer vision algorithms for edge AI vision processors, extracting and processing high-resolution video data. Tasks likely include algorithm prototyping, evaluation, and performance optimization for camera-based edge applications while collaborating with engineering teams.

Develop and maintain Linux distributions and major system components for edge AI vision processors. Responsibilities include cross-compilation, software repository maintenance, and tool development, working within open-source communities and Linux desktop environments.

Design and implement system-level software for AI vision processors used in edge camera applications. Work on low-level drivers, performance optimization for high-resolution video pipelines, hardware/software integration, and reliability for real-time inference on edge devices. Collaborate with firmware, hardware, and application teams.

Support development and evaluation of computer vision and AI algorithms optimized for edge vision processors, processing high-resolution video streams. Implement prototypes, run experiments, profile performance, and collaborate with hardware and software teams to improve accuracy and efficiency.