Computer Vision Engineer

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

Core Responsibilities

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

Role-Specific Knowledge

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

Preferred Qualifications

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)

Key Competencies

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.

What We Offer

Competitive salary and equity

Collaborative, growth-oriented team culture

Challenging AI Projects

Experience

5+ years .