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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, Metropolis Vision AI - **Company:** NVIDIA Ltd. - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $224,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Computer Vision, Profiling, Software Quality, Nvidia CUDA, Computer Engineering, Data Structures, Software Debugging, Linux, Distributed Systems, Memory Management, Python (Programming Language), Linux System Administration, Language Modeling, Performance Tuning, Software Engineering, Digital Twin, Multithreading, Pytorch, Concurrency, Deep Learning, Build Management, Information Technology, Data Analytics, Machine Learning Operations, TensorRT, Unreal Engine, Microservices - **Published:** July 10, 2026 - **Apply:** https://www.disabledperson.com/jobs/73588858-senior-software-engineer-metropolis-vision-ai ## About the Role * BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or a related field, or equivalent experience. * 12+ years of professional software development experience using modern C++ (14/17/20) and Python on Linux. * Strong computer science fundamentals, including algorithms, data structures, concurrency, and distributed systems concepts. * Demonstrated expertise in computer vision and deep learning, with a history of deploying production systems in these fields. * Experience building and debugging high-performance, concurrent systems, including multi-threading, asynchronous I/O, and efficient memory management. * Proficiency working in Linux-based environments with containers and microservices, integrating AI components into scalable back-end services. * Ability to rapidly prototype vision models and pipelines, then evolve them into production-quality services. * Practical experience with PyTorch in training, fine-tuning, and deploying models for vision tasks. * Strong analytical and problem-solving skills, with a data-driven approach to performance optimization and system build. * Excellent written and verbal communication skills, with demonstrated success collaborating across time zones and functions. Ways to stand out from the crowd: * Proven experience delivering end-to-end computer vision applications in production, such as video analytics, smart cities, autonomous systems, retail analytics, industrial inspection, or digital twins. * Practical experience with GPU acceleration (such as CUDA, TensorRT, or comparable technologies) and low-level optimization for inference and pre/post-processing. * Experience in simulation and synthetic data creation employing tools such as Omniverse, Unreal Engine, Unity, or similar digital-twin platforms. * Background in vision-language models or related multi-modal AI, including integrating these models into real products. * Background in multimedia, including video-centric processing and delivery (such as codecs, video pipelines, or media frameworks) and integrating vision models into multimedia workflows. ## Description * Crafting and implementing high-performance Vision AI pipelines for real-time and streaming scenarios using brand-new computer vision and deep learning models. * Developing and refining large-scale distributed services responsible for processing video, image, and 3D data in both edge and cloud settings. * Developing multi-modal perception capabilities that combine 2D, 3D, and temporal information to understand complex real-world scenes. * Using simulation and synthetic data tools to build, test, and validate perception algorithms at scale. * Profiling and tuning GPU-accelerated inference pipelines to meet strict latency, efficiency, and reliability targets. * Collaborating with partner teams across product, research, and platform to translate requirements into clear technical builds and robust implementations. * Driving technical build reviews, promoting guidelines for code quality and testing, and mentoring other engineers on Vision AI systems development. ## Related Videos - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [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) - [Efficient deployment and inference of GPU-accelerated LLMs​](https://www.wearedevelopers.com/videos/929-efficient-deployment-and-inference-of-gpu-accelerated-llms) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence)