Software Engineer, Metropolis Vision AI

Implementing high-performance Metropolis Vision AI pipelines for real-time and streaming scenarios using computer vision and deep learning models.

Developing large-scale distributed services responsible for processing video, image, and 3D data in both edge and cloud settings.

Assisting to 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 GPU-accelerated inference pipelines to meet strict latency, efficiency, and reliability targets.

Collaborating with partner teams to implement technical builds.

Participating in technical reviews and contributing to guidelines for code quality and testing

BS or MS in Computer Science, Electrical Engineering, or a related field, or equivalent experience.

2+ 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.

Experience in computer vision and deep learning.

Experience in implementing concurrent systems, including multi-threading, asynchronous I/O, and efficient memory management.

Experience in Linux-based environments with containers and microservices, integrating AI components into scalable back-end 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 English communication skills, with demonstrated success collaborating across time zones and functions.

Practical experience implementing 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 low-level optimization for inference and pre/postprocessing.

Experience in simulation and synthetic data creation employing tools such as

Omniverse, Unreal Engine, Unity, or similar digital-twin platforms..

Background in multimedia, including video-centric processing and delivery (such as codecs, video pipelines, or media frameworks) and integrating vision models into multimedia workflows.

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