onsite

Computer Vision Engineer

The Senior Vision AI Engineer will serve as a technical lead while remaining hands-on, architecting and deploying end-to-end Computer Vision & Deep Learning solutions. Key responsibilities include mentoring junior engineers, building and optimizing models for object detection and tracking, and deploying solutions on edge AI hardware.

About the role

About the Role

We are looking for a Senior Vision AI Engineer who can operate as a technical lead while remaining hands-on as an IC. You will architect, build, and deploy end-to-end Computer Vision & Deep Learning solutions and guide junior engineers while independently driving complex modules.

Key Responsibilities

Technical Leadership (IC + Lead)
- Lead vision AI modules end-to-end while remaining deeply hands-on.
- Mentor junior engineers through code reviews and technical guidance.
- Influence architectural decisions and own critical components of the CV pipeline.
Computer Vision & Deep Learning Engineering
- Design and develop end-to-end CV pipelines.
- Build and deploy models for object detection, tracking, segmentation, and classification.
- Train and evaluate DL models using PyTorch, TensorFlow, ONNX.
- Implement classical CV algorithms and video analytics.
Edge AI & Deployment
- Deploy optimized models on NVIDIA Jetson, Qualcomm QRide, GPU/DSP/NPU accelerators.
- Work with TensorRT, ONNX Runtime, quantization, pruning, and optimization.
- Develop high-performance C++ and Python modules for embedded CV applications.
System Design & Architecture
- Architect scalable CV systems using OOAD, SOLID, and design patterns.
- Design real-time pipelines with clear dataflows and memory management.
- Collaborate with hardware, firmware, backend, and product teams.
Deployment, Performance & MLOps
- Build production-ready inference pipelines and benchmarking systems.
- Work with Docker, CI/CD pipelines, and Git repositories.
- Support deployments across global client environments.

Required Skills & Experience

7–10 years of experience with 5+ years in Computer Vision/Deep Learning.
Strong coding in C++ (11/14/17) and Python.
Experience with CNNs (YOLO/ResNet/UNet), OpenCV, and classical CV.
Experience deploying on Jetson/DSP/NPU hardware.
Solid understanding of design patterns and system engineering.

About the role

About the Role

Key Responsibilities

Technical Leadership (IC + Lead)
- Lead vision AI modules end-to-end while remaining deeply hands-on.
- Mentor junior engineers through code reviews and technical guidance.
- Influence architectural decisions and own critical components of the CV pipeline.
Computer Vision & Deep Learning Engineering
- Design and develop end-to-end CV pipelines.
- Build and deploy models for object detection, tracking, segmentation, and classification.
- Train and evaluate DL models using PyTorch, TensorFlow, ONNX.
- Implement classical CV algorithms and video analytics.
Edge AI & Deployment
- Deploy optimized models on NVIDIA Jetson, Qualcomm QRide, GPU/DSP/NPU accelerators.
- Work with TensorRT, ONNX Runtime, quantization, pruning, and optimization.
- Develop high-performance C++ and Python modules for embedded CV applications.
System Design & Architecture
- Architect scalable CV systems using OOAD, SOLID, and design patterns.
- Design real-time pipelines with clear dataflows and memory management.
- Collaborate with hardware, firmware, backend, and product teams.
Deployment, Performance & MLOps
- Build production-ready inference pipelines and benchmarking systems.
- Work with Docker, CI/CD pipelines, and Git repositories.
- Support deployments across global client environments.

Required Skills & Experience

7–10 years of experience with 5+ years in Computer Vision/Deep Learning.
Strong coding in C++ (11/14/17) and Python.
Experience with CNNs (YOLO/ResNet/UNet), OpenCV, and classical CV.
Experience deploying on Jetson/DSP/NPU hardware.
Solid understanding of design patterns and system engineering.