Python Backend Developer - Computer vision
Dezzex
Visa & sponsorship
- Employers in UAE sponsor the residence visa by default, and nothing in the posting says otherwise.
Job description
About Dezzex Technologies
Dezzex Technologies is a pioneering enterprise software and deep-tech company based in Dubai, specializing in advanced artificial intelligence, computer vision, digital twins, and autonomous drone software platforms. We engineer high-performance, sovereign AI solutions—including our flagship CAMEX video analytics platform—deployed across retail, healthcare, smart cities, and municipal infrastructure throughout the GCC region.
We are scaling our engineering core and looking for a Senior Python Developer with deep expertise in Computer Vision, NVIDIA DeepStream, and TensorRT to lead the architecture, optimization, and edge deployment of our enterprise video analytics pipelines.
Role Overview
As a Senior Python Developer at Dezzex, you will take ownership of high-throughput video ingestion pipelines, real-time object detection/tracking models, and edge-to-cloud inference optimization. You will bridge the gap between advanced deep learning research and industrial-grade production deployments, ensuring our computer vision solutions run with ultra-low latency, high concurrency, and robust reliability across enterprise hardware (NVIDIA Jetson and datacenter GPUs).
Key Responsibilities
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Pipeline Architecture & Optimization: Design, build, and optimize end-to-end real-time computer vision pipelines utilizing NVIDIA DeepStream SDK and GStreamer for multi-stream RTSP/ONVIF camera ingestion.
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Model Acceleration & Deployment: Convert, quantize (FP16/INT8), and deploy deep learning models (PyTorch/TensorFlow) using TensorRT to maximize throughput and minimize latency on target hardware.
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Core Computer Vision & Analytics: Implement and scale advanced algorithms for object detection, tracking (DeepSORT/ByteTrack), facial recognition, anomaly detection, and spatial analytics.
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System Integration: Integrate video analytics telemetry, metadata streams, and event triggers with backend architectures via REST APIs, WebSockets, MQTT, and databases (PostgreSQL/Redis).
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Performance Tuning & Scalability: Profile memory usage, GPU utilization, and CPU bottlenecks to ensure seamless scaling across multi-camera edge deployments and enterprise servers.
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Code Quality & Mentorship: Establish rigorous software engineering standards, write clean, maintainable Python/C++ code, conduct code reviews, and mentor mid-level engineers and computer vision interns.
Technical Requirements & QualificationsCategoryRequirementsExperience5+ years of software engineering experience, with at least 3+ years focused specifically on production-grade Computer Vision and Video Analytics.Core LanguagesExpert-level proficiency in Python; solid working knowledge or integration experience with C++.CV & Deep Learning FrameworksStrong command of PyTorch or TensorFlow, OpenCV, and object tracking frameworks.Inference & Streaming StacksDeep hands-on experience with NVIDIA DeepStream SDK, TensorRT, GStreamer, and video protocols (RTSP, RTMP, ONVIF Profile S/T/G/M).Hardware & InfrastructureExperience deploying models on NVIDIA Jetson edge devices (Orin/Nano) as well as enterprise datacenter GPUs (Ada Lovelace / Ampere architectures).Containerization & DevOpsProficient with Docker, Linux system administration (Ubuntu/RHEL), and edge orchestration tools.What We Offer
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High-Impact Leadership: Direct influence over core product architecture and next-generation video analytics solutions deployed at scale across the region.
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Cutting-Edge Hardware: Access to high-performance computing clusters, custom workstations, and modern enterprise AI development rigs.
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Dynamic Growth Environment: A fast-paced, innovation-driven culture working alongside top-tier AI and full-stack engineering teams in Dubai.
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Competitive Remuneration: Attractive tax-free salary package commensurate with experience, along with performance incentives.
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send CV hiring@dezzex.com
Pay: AED15,000.00 - AED25,000.00 per month
Work Location: In person