Stepping Edge
Website:
steppingedge.com
Job details:
We are seeking an experienced Senior Computer Vision Engineer to join our AI team. In this role, you will design, implement, and deploy state-of-the-art computer vision models and algorithms to solve complex real-world problems. You will be responsible for the entire development lifecycle, from initial research and prototyping to production-level deployment and optimization.
Responsibilities
- Design and develop advanced computer vision algorithms for tasks such as object detection (YOLO, Faster R-CNN, etc.), segmentation, tracking, and feature extraction.
- Implement and train deep learning models using frameworks like PyTorch or TensorFlow, with a focus on modern neural network architectures.
- Optimize and deploy vision algorithms for real-time performance on various hardware platforms, specifically Cloud (AWS/GCP/Azure) and Edge devices (NVIDIA Jetson, Coral, etc.).
- Apply OpenCV and other libraries for image transformation, filtering, and data augmentation pipelines.
- Stay current with the latest research in computer vision and deep learning, applying relevant breakthroughs to our products.
- Collaborate with software engineers to integrate vision components into larger systems and APIs.
- Mentor junior engineers and participate in code reviews to maintain high engineering standards.
Required Qualifications
- Education: Bachelor’s degree in Computer Science, Electrical Engineering, or a related field.
- Experience: 4+ years of professional experience in developing and deploying computer vision solutions in a production environment.
- Programming: Expert proficiency in Python and C++.
- Deep Learning: Hands-on experience with PyTorch or TensorFlow, with specific expertise in YOLO and diverse neural model architectures.
- Vision Libraries: Extensive experience with OpenCV, specifically for image transformations, preprocessing, and traditional vision techniques.
- Deployment: Proven track record of deploying models to Cloud environments and optimizing for Edge devices.
Preferred Skills
- Experience with deployment tools such as TensorRT, ONNX, or OpenVINO.
- Familiarity with cloud infrastructure (AWS/GCP/Azure) and MLOps practices.
- Experience with Docker and Kubernetes for model deployment.
- Contributions to open-source projects or publications in top-tier conferences (CVPR, ICCV, ECCV).
Soft Skills
- Strong analytical and problem-solving abilities.
- Excellent communication skills to explain complex technical concepts to non-technical stakeholders.
- Ability to work effectively in a fast-paced, collaborative team environment.
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