Senior Embedded AI Researcher
Description We are looking for a highly skilled and motivated engineer to join our team at the intersection of AI research and embedded systems. In this role, you will be responsible for bringing our cutting-edge computer vision models to life on our Ambarella CVxx-based dash cams. You will work closely with our research engineers to optimize and deploy neural networks for tasks such as object detection, video reconstruction, and collision prediction, all within the resource-constrained environment of an embedded system. This is a unique opportunity to have a major impact on the performance and capabilities of our products, and to help shape the future of AI in the automotive industry. You Are a Good Fit If You
- Get excited about squeezing 10% more performance from a carefully tuned operator
- Can explain both ResNet architecture and L2 cache eviction policies
- Think about problems from both "what model architecture works best?" and "can this fit in 512MB of RAM?"
- Enjoy working at the intersection of research innovation and engineering pragmatism
- Are energised by the constraints of real-time, power-limited embedded systems
- Develop, optimize, and deploy deep learning models on our Ambarella CVFlow-based camera platforms, or future replacements in the future.
- Bridge the gap between our research and systems engineering teams, translating state-of-the-art AI models into highly efficient, production-ready code.
- Dive deep into the Ambarella CVFlow architecture to maximize the performance of our neural networks, leveraging your expertise in computer vision, hardware acceleration, and low-level programming.
- Analyze and profile model performance, identifying and addressing bottlenecks related to I/O, memory, and compute.
- Implement and experiment with model optimization techniques such as quantization, pruning, knowledge distillation strategies and network architecture search to meet strict latency and power budgets, while managing precision / recall and accuracy targets.
- Develop custom operators and layers optimized for CVflow's vision processing engine.
- Work with our systems engineers to design, implement and ultimately ensure the seamless integration of AI models with camera firmware and software.
- Stay up-to-date with the latest advancements in embedded AI, GenAI, and computer vision.
- BS/MS/PhD in Computer Science, Electrical Engineering, or related field
- 3+ years of industry experience in embedded ML, edge AI, or related domains
- Track record of shipping ML models in production embedded systems
- Proficiency in C/C++ for embedded systems and performance-critical code.
- Understanding of computer architecture: cache hierarchies, memory systems, SIMD/vector processing.
- Knowledge of DMA, interrupts, and hardware-software interfaces.
- Hands-on experience with embedded AI platforms and hardware accelerators (e.g., Ambarella CVFlow, NVIDIA Jetson, Qualcomm Hexagon).
- Deep understanding of computer architecture, including concepts like kernel scheduling, I/O, memory management, and GPU/NPU pipelines.
- Experience with heterogeneous computing (CPU/GPU/NPU/DSP coordination).
- Prior experience deploying neural networks to resource-constrained devices (mobile, automotive, IoT)
- Professional experience with deep learning frameworks such as TensorFlow, PyTorch, or Caffe.
- Direct experience with Ambarella SoCs and CVflow architecture
- Background in computer vision applications (object detection, segmentation, tracking)
- Experience with automotive ADAS development and safety standards
- Knowledge of video codec integration (H.264/H.265)
- Understanding of fixed-point arithmetic and numerical stability
- Experience with TensorRT, LiteRT, ONNX Runtime, or similar inference engines
- Contributions to ML deployment frameworks or toolchains
- The chance to have a meaningful and positive impact on roads and cities’ safety
- Flexibility - in schedule, work location, benefits
- Competitive compensation
- A fast-paced work environment full of kind, smart, and highly driven people
- Great professional and personal growth opportunities
- Regular team-building events and well-being initiatives/facilities