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NVIDIA

Designs the chips and software that power AI

Senior Software Engineer - Metropolis Vision AI

Computer VisionUpdated on Oct 31
Full-timeIn-person

About the Job

Requirements

  • A BS, MS, or PhD in Computer Science, Electrical Engineering, or Computer Engineering, 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 and a focus on Vision-Language Models.
  • 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.

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 responsible for processing video, image, and 3D data in edge and cloud settings.
  • Develop multi-modal perception capabilities that combine 2D, 3D, and temporal information to understand complex 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 partner teams across product, research, and platform to translate requirements into technical builds and robust implementations.
  • Drive technical build reviews, promote guidelines for code quality and testing, and mentor other engineers on Vision AI systems development.

Desired Qualifications

  • 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 using 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.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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