Senior Software Engineer, Metropolis Vision AI

NVIDIA•Santa Clara, CA

10d•$224,000 - $356,500

About The Position

NVIDIA’s Metropolis team builds large-scale distributed Vision AI platforms for intelligent spaces, smart cities, retail analytics, and digital twins. The Senior Software Engineer will develop and optimize high-performance vision systems that turn large streams of video, image, and 3D data into actionable insights. The role involves owning core components of a strategic, high-visibility platform and collaborating with specialists in perception, simulation, and large models to bring research into production at scale. The engineer will build real-time and streaming Vision AI pipelines, develop distributed services for edge and cloud environments, create multimodal perception capabilities, and use simulation and synthetic data to test algorithms. The position also focuses on GPU-accelerated inference performance, cross-functional implementation, technical reviews, code quality, testing, and mentoring.

Requirements

BS, MS, or PhD in Computer Science, Electrical or 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, including a history of deploying production systems with a focus on Vision-Language Models (VLMs).
Experience building and debugging high-performance concurrent systems, including multithreading, asynchronous I/O, and efficient memory management.
Proficiency in Linux-based environments with containers and microservices, integrating AI components into scalable backend services.
Ability to rapidly prototype vision models and pipelines and evolve them into production-quality services.
Practical experience using PyTorch to train, fine-tune, and deploy models for vision tasks.
Strong analytical and problem-solving skills, with a data-driven approach to performance optimization and system development.
Excellent written and verbal communication skills, including success collaborating across time zones and functions.

Nice To Haves

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 technologies such as CUDA or TensorRT, and low-level inference and pre/post-processing optimization.
Experience with simulation and synthetic data creation using Omniverse, Unreal Engine, Unity, or similar digital-twin platforms.
Background in vision-language models or related multimodal 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.

Responsibilities

Craft and implement high-performance Vision AI pipelines for real-time and streaming scenarios using computer vision and deep learning models.
Develop and refine large-scale distributed services that process video, image, and 3D data in edge and cloud settings.
Develop multimodal perception capabilities combining 2D, 3D, and temporal information to understand real-world scenes.
Use simulation and synthetic data tools to build, test, and validate perception algorithms at scale.
Profile and tune GPU-accelerated inference pipelines to meet latency, efficiency, and reliability targets.
Collaborate with product, research, and platform teams to translate requirements into technical designs and robust implementations.
Lead technical build reviews, promote code quality and testing guidelines, and mentor engineers in Vision AI systems development.