Job Description

Computer Vision Engineer

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Experience

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4+ years of hands-on experience in Computer Vision, AI/ML model development, and production deployment

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Role Overview

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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.

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Key Responsibilities

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· Design, develop, and deploy computer vision solutions for image and video data

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· Implement, fine-tune, and optimize object detection models (YOLO, SSD, Faster R-CNN, etc.)

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· Build real-time inference pipelines with low latency and high reliability

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· Collaborate with backend teams to expose models via APIs and services

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· Own production deployment across cloud, on-prem, and edge devices

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· Optimize models for performance, scalability, and cost efficiency

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· Lead technical discussions, guide the team, and review code/model designs

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· Maintain documentation for models, deployments, and system architecture

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Required Technical Skills

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Computer Vision & AI

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· Robust fundamentals in Computer Vision and Deep Learning





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· Hands-on experience with object detection, tracking, and video analytics

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· Proficiency with OpenCV for image and video processing

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LLM & Generative AI

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· Experience working with Large Language Models (LLMs)

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· Knowledge of integrating CV outputs with LLMs (multimodal pipelines, RAG, AI agents, etc.)

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· Familiarity with LLM APIs, prompt engineering, and inference optimization

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· Understanding of real-world LLM deployment constraints (latency, cost, scaling)

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Programming & Frameworks

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· Strong proficiency in Python

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· Experience with PyTorch or TensorFlow

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· Familiarity with dataset annotation, versioning, and experiment tracking

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Deployment & Infrastructure

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· Proven experience deploying AI models into production environments

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· Strong understanding of GPU-based inference and acceleration

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· Experience with edge AI devices (e.g., NVIDIA Jetson or similar)

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· Knowledge of model optimization tools (ONNX, TensorRT, quantization, pruning)

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· Experience with Docker and containerized deployments

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· Exposure to CI/CD pipelines for ML or MLOps workflows

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Education

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Bachelor’s or Master’s degree in Computer Science, AI/ML, Electronics, or related fields

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