Computer Vision Engineer Experience 4 years of hands-on experience in Computer Vision, AI/ML model development, and production deployment Role Overview We are looking for a skilled Computer Vision Engineer who can design, develop, deploy, and lead real-world AI solutions. The role involves building image/video analytics systems, integrating LLM-powered components, and taking ownership of end-to-end deployment across cloud, on-prem, and edge environments. The ideal candidate should also demonstrate technical leadership and mentoring capabilities. Key Responsibilities · Design, develop, and deploy computer vision solutions for image and video data · Implement, fine-tune, and optimize object detection models (YOLO, SSD, Faster R-CNN, etc.) · Build real-time inference pipelines with low latency and high reliability · Collaborate with backend teams to expose models via APIs and services · Own production deployment across cloud, on-prem, and edge devices · Optimize models for performance, scalability, and cost efficiency · Lead technical discussions, guide the team, and review code/model designs · Maintain documentation for models, deployments,



and system architecture Required Technical Skills Computer Vision & AI · Solid fundamentals in Computer Vision and Deep Learning · Hands-on experience with object detection, tracking, and video analytics · Proficiency with OpenCV for image and video processing LLM & Generative AI · Experience working with Large Language Models (LLMs) · Knowledge of integrating CV outputs with LLMs (multimodal pipelines, RAG, AI agents, etc.) · Familiarity with LLM APIs, prompt engineering, and inference optimization · Understanding of real-world LLM deployment constraints (latency, cost, scaling) Programming & Frameworks · Strong proficiency in Python · Experience with PyTorch or TensorFlow · Familiarity with dataset annotation, versioning, and experiment tracking Deployment & Infrastructure · Proven experience deploying AI models into production environments · Strong understanding of GPU-based inference and acceleration · Experience with edge AI devices (e.g., NVIDIA Jetson or similar) · Knowledge of model optimization tools (ONNX, TensorRT, quantization, pruning) · Experience with Docker and containerized deployments · Exposure to CI/CD pipelines for ML or MLOps workflows Education Bachelor’s or Master’s degree in Computer Science, AI/ML, Electronics, or related fields

📌 Computer Vision Engineer (Kerala)
🏢 Difinity Digital
📍 Kerala