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Senior Embedded AI Engineer

10 hours ago

Chennai, Tamil Nadu, India e-con Systems Full time

Company Description

e-con Systems has been a pioneer in designing, developing, and manufacturing custom and off-the-shelf OEM camera solutions since 2003. With expertise across industries like smart retail, medical imaging, biometrics, and mobility, our cameras are trusted globally by over 350 customers and are embedded in a wide range of innovative products. We specialize in advanced camera technologies including MIPI, GMSL, and AI-supported smart cameras, offering features like HDR, low-light performance, and multi-camera synchronization. With 2 million cameras shipped worldwide, we ensure high standards of quality compliance, meeting ISO certifications for automotive and medical industries. Leveraging a powerful partner ecosystem and providing long-term support, e-con Systems delivers reliable and customizable end-to-end vision solutions.

Role Description

We are seeking a Senior Embedded AI Engineer for a full-time, on-site role located in Tamil Nadu, India. Responsibilities include developing and implementing AI algorithms for embedded systems, integrating machine learning models for real-time performance optimization, and collaborating with cross-functional teams to create cutting-edge computer vision applications. The role also involves analyzing hardware constraints to ensure efficient use of resources in camera systems and debugging and fine-tuning AI models for deployment in various industry applications.

Responsibilities :

  • Algorithm Development:
    Design, implement, and optimize computer vision and deep learning algorithms for object detection, segmentation, 3D reconstruction, OCR, anomaly detection, and pose estimation
  • End-to-End Pipeline Ownership:
    Develop and maintain robust vision pipelines, encompassing data ingestion, preprocessing, inference, post-processing, and system integration
  • Quantization-Aware Training (QAT):
    Implement and fine-tune QAT techniques to optimize CV model performance and reduce memory footprint while maintaining accuracy on vision tasks.
  • Model Optimization:
    Apply advanced optimization methods—including pruning, quantization (PTQ and QAT), knowledge distillation, and architecture tweaks—to meet strict latency, power, and memory requirements for real-time vision applications.
  • Runtime Integration:
    Integrate optimized computer vision models with embedded runtime environments, hardware accelerators, and edge AI camera pipelines.
  • Performance Profiling & Tuning:
    Profile and analyze CV model performance on target embedded hardware, identify bottlenecks in pre/post-processing or inference, and implement optimizations for real-time video processing.
  • Toolchain Development & Utilization:
    Use and contribute to custom conversion tools, optimization scripts, and automated deployment pipelines for computer vision model deployment.

Skills Required :

  • Experience:
    2+ years in embedded software development with a strong focus on deploying computer vision AI models to edge devices.
  • Programming Skills:
    Proficiency in Python for CV model development, training, and scripting.
  • Deep Learning Frameworks:
    Strong hands-on experience with PyTorch for computer vision tasks; TensorFlow/Keras experience is a plus.
  • Embedded Systems:
    Solid understanding of embedded architectures, microcontrollers, DSPs, FPGAs, and edge AI hardware used in vision systems.
  • Optimization Techniques:
    Demonstrated experience with optimization methods such as quantization, pruning, and knowledge distillation specifically for computer vision workloads.
  • Conversion Tools:
    Experience with model conversion and deployment tools like ONNX, OpenVINO and TensorRT for vision models.
  • Problem-Solving:
    Strong analytical and debugging skills for optimizing complex CV systems from model to hardware.
  • C/C++ Knowledge:
    Experience with C/C++ for performance-critical embedded software components.
  • Embedded Integration:
    Collaborate with embedded engineers to port and optimize vision software for various hardware platforms (SoCs, GPUs, NPUs)

If you're eager to build industry leading AI-powered vision technologies, we'd love to hear from you

Send your resume to
prakash.-
, and feel free to share this opportunity with someone who might be a great fit.