Senior Vision Systems Engineer

Luxoft; Dubai; On-site; AED 300,000 - 420,000; Full time

Job summary

Luxoft seeks a hands‑on technical leader to design, optimize, and productize high‑performance computer vision and AI pipelines for embedded consumer devices. This role ensures real‑time performance, power efficiency, and production robustness across embedded platforms.

You will design CV pipelines, deploy ML models on edge devices, and mentor engineers while collaborating with Android/Linux teams to ensure scalable, testable solutions with strong KPIs like FPS and latency.

Qualifications

• Requires 7-10+ years in computer vision and image processing.
• Proven track record shipping embedded vision/AI products.
• Strong C++ 14/17/20 with optimization for real-time systems.
• Expertise with OpenCV and ML frameworks (PyTorch, TensorFlow, ONNX).
• Experience deploying ML models on embedded/edge devices.
• Experience with model optimization (quantization, pruning).
• Solid understanding of 2D/3D geometry and linear algebra.
• Experience with embedded Linux or Android.
• Proficient debugging and performance profiling.
• Ability to optimize for power and thermal constraints.

Responsibilities

• Design and implement real-time CV and image processing pipelines for consumer devices.
• Collaborate with ISP, sensor, and tuning teams to optimize image quality for AI and UX.
• Develop and deploy ML models for visual recognition and scene understanding.
• Optimize ML models for edge deployment (quantization, pruning, distillation).
• Implement performance-critical algorithms in modern C++ for embedded platforms.
• Profile and optimize latency, power, memory, and thermal metrics.
• Integrate inference engines (TFLite, TensorRT, ONNX Runtime) on target SoCs.
• Work with Android/Linux teams to integrate camera and AI pipelines.
• Define and track KPIs: FPS, power, memory, startup time, accuracy.
• Mentor engineers and review architecture proposals.

Skills

C++ optimization

OpenCV

PyTorch

TensorFlow

ONNX

Embedded Linux/Android

Performance profiling

2D/3D geometry

ML model deployment

Camera ISP integration

Education

Bachelor's or Master's in CS/EE

Tools

CUDA

OpenCL

Vulkan

OpenGL ES

SIMD

YOCTO

Android Camera HAL

Job description

Project description

hands‑on technical leader responsible for designing, optimizing, and productizing high‑performance computer vision and AI pipelines for consumer devices. This role ensures real‑time performance, power efficiency, and production robustness across embedded platforms.

Responsibilities

• Design and implement advanced computer vision and image processing pipelines optimized for real‑time consumer devices.
• Collaborate with ISP, sensor, and tuning teams to optimize image quality for downstream AI and UX performance.
• Develop and deploy ML models for visual recognition, enhancement, tracking, or scene understanding.
• Optimize ML models for edge deployment (quantization, pruning, distillation, hardware‑aware tuning).
• Implement performance‑critical algorithms in modern C++ for embedded platforms.
• Optimize for latency, power consumption, memory footprint, and thermal constraints.
• Integrate inference engines (TFLite, TensorRT, ONNX Runtime, etc.) on target SoCs.
• Work closely with Android/Linux platform teams to integrate camera and AI pipelines.
• Define and track KPIs: FPS, power usage, memory, startup time, and accuracy.
• Profile and optimize performance across CPU/GPU/NPU/DSP.
• Drive debugging of complex system‑level issues in production builds.
• Ensure robust unit testing and contribute to automated validation pipelines.
• Mentor engineers and review architecture/design proposals.
• Support product bring‑up and mass production readiness.

Skills

Must have

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field.
• 7-10+ years of experience in computer vision/image processing.
• Proven experience shipping at least one consumer product with embedded vision/AI.
• Strong C++ expertise (C++14/17/20), including performance optimization.
• Strong experience with OpenCV and ML frameworks (PyTorch, TensorFlow, ONNX).
• Experience deploying ML models on embedded/edge devices.
• Experience with model optimization (quantization, pruning).
• Strong understanding of 2D/3D geometry and linear algebra.
• Experience working on embedded Linux or Android systems.
• Strong debugging and performance profiling skills.
• Experience optimizing for power and thermal constraints.

Nice to have

• Experience with mobile SoCs (Qualcomm, MediaTek, Exynos, etc.).
• Experience with CUDA / OpenCL / Vulkan / OpenGL ES / SIMD.
• Experience with camera calibration and ISP interaction.
• Experience building for Android Camera HAL or Yocto‑based systems.
• Experience with AR, computational photography, or video processing.
• Experience with multi‑camera systems.
• Exposure to production validation and manufacturing constraints.

Other

Languages

English: B2 Upper Intermediate

Seniority

Lead