This role has closed. Ambarella has taken the posting down.
hirly last saw it live on 30 September 2026. See similar open roles below, or browse the live board.
Ambarella
Edge Computer Vision Accelerator Engineer
Taiwan Hsinchu
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hirly's read of this role
- Seniority
- Mid level
- Country
- TW
- Work mode
- On-site / unstated
- First seen by hirly
- 2 Sept 2026
Derived automatically from the posting.
the posting
AI Vision Processors For Edge Applications
Our solutions make cameras smarter by extracting valuable data from high-resolution video streams.
Job Description
Join us to build Classical CV and NNISP acceleration pipelines on CVflow, and improve system performance and efficiency.
We are looking for engineers passionate about embedded systems and computer vision — fresh graduates and experienced candidates are welcome.
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About the Team
We are the CV Accelerator team within the DSP department,focused on delivering high-performance edge-side computer vision processing on Ambarella’s proprietary CVflow™ architecture.
Our work targets real-world applications requiring low latency, low power, and real-time performance at the edge.
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What You’ll Do
Port and optimize classical (non-neural-network) computer vision algorithms onto CVflow (e.g., image processing, filtering, optical flow, radar/LiDAR point cloud processing)
Perform NNISP model porting for neural network–based ISP pipelines
Develop efficient implementations on:
NVP (Neural Vector Processor)
GVP (General Vector Processor)
Optimize compute performance and memory efficiency
Ensure real-time performance on edge hardware platforms
Leverage modern AI-assisted coding tools to improve productivity
Collaborate with cross-functional teams (algorithm / system / hardware)
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Why Join Us
Work on edge AI / computer vision acceleration hardware (CVflow)
Gain experience in both classical CV and NNISP pipelines
Tackle real-world performance-critical systems
Grow into an expert in edge computer vision and hardware-aware optimization
Be part of a team using modern, high-productivity development workflows
Preferred Qualifications
Familiarity with embedded systems (ARM-based)
Understanding of multithreading (Linux or RTOS)
Experience in debugging and performance optimization
Background in image processing or computer vision is a strong plus
Familiarity with Python or deep learning frameworks (e.g., PyTorch) is a plus, especially for NNISP-related development
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Nice to Have
Experience with edge AI or computer vision pipelines
Exposure to hardware accelerators, SIMD, or vector processing
Experience with AI-assisted coding tools (e.g., Cursor or similar)
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Experience Level
Fresh graduates are welcome
Candidates with relevant experience are preferred