At Codvo, software and people transformations go together.

We are a global empathy-led technology services company with a core DNA of product innovation and mature software engineering.

We uphold the values of Respect, Fairness, Growth, Agility, and Inclusiveness in everything we do.

Job Overview:

We are seeking a Senior Computer Vision Edge AI Engineer (5+ years of experience) to architect, develop, and deploy high-performance computer vision systems for real-time applications.

This role requires deep expertise in object detection, segmentation, tracking, and pose estimation, along with strong experience in optimizing and deploying deep learning models on edge platforms such as NVIDIA Jetson, Intel-based devices, and NVIDIA IGX Orin.

Key Responsibilities:

- Design, develop, and optimize computer vision models for:

a. Object Detection.

b. Image & Instance Segmentation.

c. Multi-Object Tracking.

d. Human Pose Estimation.

- Build and train deep learning models using frameworks such as PyTorch or TensorFlow.

- Convert and optimize models for edge deployment using:

- TensorRT.

- OpenVINO.

- NVIDIA TAO Toolkit.

- Perform model quantization, pruning, benchmarking, and latency optimization.

- Deploy models on edge hardware platforms (NVIDIA Jetson, Intel-based edge devices, NVIDIA IGX Orin, etc.

- Write clean, scalable, and production-ready Python code.

- Collaborate with cross-functional teams including ML engineers, software developers, and hardware teams.

- Conduct performance evaluation, debugging, and continuous improvement of deployed systems.

- Stay updated with the latest research and advancements in computer vision and edge AI.

Required Qualifications:

- 5+ years of hands-on experience in Computer Vision and Deep Learning.

- Strong expertise in:

a. Object detection architectures (e.g., YOLO, Faster R-CNN, SSD).

b. Segmentation models (e.g., U-Net, Mask R-CNN).

c. Tracking algorithms (e.g., DeepSORT, ByteTrack).

d. Pose estimation frameworks (e.g., OpenPose, HRNet).

- Proven experience deploying optimized models using:

a. TensorRT.

b. OpenVINO.

c. NVIDIA TAO Toolkit.

d. Strong Python programming skills.

- Experience with model optimization techniques (INT8 quantization, FP16, pruning).

- Familiarity with ONNX and model conversion pipelines.

- Strong understanding of GPU acceleration and edge hardware constraints.