Computer Vision Engineer
Stepping Edge
- Design, develop, and deploy computer vision models for tasks such as object detection, segmentation, tracking, classification, and image/video analysis
- Own the full ML pipeline: data collection and labeling strategy, model training, evaluation, and production deployment
- Optimize models for performance, latency, and efficiency on target hardware (cloud, edge, or embedded devices)
- Collaborate with cross-functional teams to translate business requirements into technical solutions
- Build and maintain robust data pipelines and MLOps infrastructure for training and inference
- Debug and improve model performance through rigorous experimentation and error analysis
- 5+ years of hands-on experience building and deploying computer vision systems in production
- Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or similar)
- Solid understanding of core CV techniques: CNNs, object detection (YOLO, Faster R-CNN, etc.), segmentation, image processing fundamentals
- Experience with model optimization and deployment (ONNX, TensorRT, quantization, edge deployment, or cloud inference services)
- Familiarity with MLOps tools and practices (experiment tracking, CI/CD for ML, model versioning)
- Strong software engineering fundamentals - clean code, version control, testing
- Excellent problem-solving skills and ability to work independently in a fast-paced environment
- Must have experience in any one of the domains and deployment areas mentioned below.
- Domain experience: Robotics, Healthcare, autonomous vehicles, retail/Manufacturing automation.
- Deployment experience: Edge devices (NVIDIA Jetson), Cloud Platforms (AWS, GCP, Azure), or hybrid edge cloud setups.
- Background in generative vision models (diffusion models, GANs) or vision-language models
- Publications or contributions to open-source CV/ML projects
- Experience with real-time video processing systems
- Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)
- Analytical and problem-solving skills.
- Innovation and research mindset.
- Strong communication and collaboration skills.
- Attention to detail.
- Ownership and accountability.
- Ability to mentor and guide technical teams.
- Competitive salary and equity
- Collaborative, growth-oriented team culture
- Challenging AI Projects
- 5+ years
- Send your details to [email protected]