Computer Vision Engineer

Stepping Edge; Coimbatore District; On-site; INR 1,500,000 - 2,800,000; Full time

Benefits offered by this job

Competitive salary

Equity

Job summary

Stepping Edge in India is seeking a seasoned computer vision engineer to design, develop, and deploy vision systems for object detection, segmentation, tracking, and analysis. You will own end-to-end ML pipelines from data collection to production deployment.

The role emphasizes optimizing models for latency on cloud, edge or embedded devices, collaborating with cross-functional teams, and building robust MLOps infra for training and inference.

Qualifications

• 5+ years of hands-on experience building and deploying computer vision systems in production.
• Strong Python and deep learning frameworks (PyTorch or TensorFlow).
• Solid CV techniques: CNNs, object detection, segmentation.
• Experience with model optimization and deployment (ONNX, TensorRT, edge deployment, or cloud inference services).
• Familiarity with MLOps, CI/CD for ML, and model versioning.

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

Skills

Python

PyTorch

TensorFlow

Object detection

Image segmentation

MLOps

CI/CD

Docker

Kubernetes

Version control

Edge deployment

Tools

Docker

Kubernetes

ONNX

TensorRT

AWS

GCP

Job description

• 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