Senior Vision Systems Engineer - Real-Time Embedded AI

Luxoft; Malaysia; Remote; MYR 180,000 - 260,000; Full time

Job summary

Luxoft Germany seeks an experienced Computer Vision Engineer to design and optimize real-time CV pipelines for consumer devices. You will work with ISP, sensors, and tuning teams to enhance image quality for downstream AI and UX, and deploy ML models on edge hardware.

You will optimize models for power, latency, and memory, implement algorithms in C++, and collaborate across Android/Linux platform teams to ensure robust production readiness.

Qualifications

• Bachelor's or Master's in CS, EE or related field.
• 7-10+ years of experience in computer vision/image processing.
• Proven experience shipping consumer products with embedded vision/AI.
• Strong C++ expertise (C++14/17/20) and performance optimization.
• Experience with OpenCV and ML frameworks (PyTorch/TF/ONNX).
• Experience deploying ML models on embedded/edge devices.

Responsibilities

• Design and implement advanced CV and image pipelines for real-time devices.
• Collaborate with ISP, sensor, and tuning teams to optimize image quality.
• Develop and deploy ML models for visual recognition and tracking.
• Optimize ML models for edge deployment (quantization, pruning).
• Implement performance-critical algorithms in modern C++ for embedded platforms.
• Profile and optimize performance across CPU/GPU/NPU/DSP and power/thermal usage.
• Integrate inference engines on target SoCs and work with Android/Linux teams.
• Define KPIs like FPS, power usage, memory, startup time, accuracy.

Skills

10+ years CV/vision

C++ performance

OpenCV expertise

ML frameworks experience

Edge device deployment

Profiling & debugging

Education

Bachelor's or Master's in CS/EE

Tools

OpenCV

CUDA/OpenCL

Vulkan/OpenGL ES

Job description

Luxoft Germany seeks an experienced Computer Vision Engineer to design and optimize real-time CV pipelines for consumer devices. You will work with ISP, sensors, and tuning teams to enhance image quality for downstream AI and UX, and deploy ML models on edge hardware.

You will optimize models for power, latency, and memory, implement algorithms in C++, and collaborate across Android/Linux platform teams to ensure robust production readiness.