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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Application Engineer - **Company:** EchoTwin AI, Inc. - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Artificial Neural Networks, Computer Vision, C++ (Programming Language), Cloud Computing, Nvidia CUDA, Computer Programming, Software Debugging, Linux, Python (Programming Language), Machine Learning, Object Detection, OpenCV, Systems Development Life Cycle, Tensorflow, Smart Devices, Software Engineering, Systems Architecture, Systems Integration, Graphics Processing Unit (GPU), Real Time Systems, Pytorch, Containerization, Information Technology, TensorRT, Hardware Infrastructure, Docker - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/application-engineer-computer-vision-echotwin-ai-8116285 ## About the Role We are seeking a skilled Application Engineer to join our team, focusing on deploying and optimizing computer vision systems on NVIDIA Jetson platforms. The ideal candidate will have expertise in embedded systems, computer vision, and software development, with a passion for delivering high-performance solutions in real-world applications., * Bachelor's or Master's degree in Computer Science, Electrical Engineering, Robotics, or a related field. A PhD is a plus. * 3+ years of experience in developing and deploying computer vision or machine learning applications. * Hands-on experience with NVIDIA Jetson platforms and associated tools (JetPack SDK, DeepStream, TensorRT). * Proficiency in programming languages such as Python, C++, and CUDA. * Experience with computer vision libraries/frameworks (e.g., OpenCV, PyTorch, TensorFlow). * Familiarity with Linux-based development and embedded systems. * Strong understanding of computer vision algorithms (e.g., CNNs, YOLO, Transformer, image processing techniques). * Knowledge of optimizing neural networks for edge devices (e.g., model quantization, pruning). * Experience with hardware-software integration, including cameras, sensors, and GPUs. * Excellent problem-solving and debugging skills. * Strong communication and teamwork abilities. * Familiarity with cloud-edge architectures for computer vision applications. * Knowledge of containerization tools (e.g., Docker) for deployment. * Prior work in industries such as autonomous vehicles, robotics, or IoT. ## Description * System Development and Deployment: Design, develop, and deploy computer vision applications on NVIDIA Jetson platforms (e.g., Jetson Xavier, Orin, Thor). * Algorithm Optimization: Optimize computer vision algorithms (e.g., object detection, image segmentation, tracking) for performance, power efficiency, and real-time processing on resource-constrained devices. * Integration: Integrate computer vision pipelines with hardware components, sensors, and peripheral devices, ensuring seamless operation in embedded environments. * Software Development: Write clean, efficient, and maintainable code in Python, C++, or CUDA for computer vision tasks, leveraging NVIDIA's JetPack SDK, DeepStream, and TensorRT. * Testing and Validation: Conduct rigorous testing, debugging, and validation of computer vision systems to ensure reliability, accuracy, and robustness in diverse scenarios. * Collaboration: Work closely with cross-functional teams, including data scientists, hardware engineers, and product managers, to align solutions with project requirements. * Documentation: Create detailed documentation for code, system architecture, and deployment processes to support team collaboration and future maintenance. * Stay Updated: Keep abreast of advancements in computer vision, embedded systems, and NVIDIA technologies to recommend innovative solutions. ## Related Videos - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [Trends, Challenges and Best Practices for AI at the Edge](https://www.wearedevelopers.com/videos/630-trends-challenges-and-best-practices-for-ai-at-the-edge) - [Deepfakes in Realtime - How Neural Networks Are Changing Our World](https://www.wearedevelopers.com/videos/180-deepfakes-in-realtime-how-neural-networks-are-changing-our-world) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Docker exec without Docker](https://www.wearedevelopers.com/videos/1094-docker-exec-without-docker) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Where To Find Software Engineering Jobs](https://www.wearedevelopers.com/magazine/396-where-to-find-software-engineering-jobs)