Computer Vision Engineer

Difinity Digital; Ernakulam; On-site; INR 1,400,000 - 2,200,000; Full time

Job summary

Difinity Digital in Kerala, India seeks a seasoned Computer Vision Engineer to design, develop, deploy, and lead real-world AI solutions. The role focuses on building image and video analytics systems, integrating LLM-powered components, and owning end-to-end deployment across cloud, on-prem, and edge environments.

The ideal candidate brings 4+ years of hands-on CV/AI experience, strong Python and DL framework skills, and the ability to mentor a team while optimizing models for performance and

Qualifications

• Bachelor’s or Master’s in CS/AI/related fields.
• 4+ years hands-on CV/AI model development and deployment.
• Experience deploying AI models to production environments.
• Proficiency with Python and DL frameworks (PyTorch/TensorFlow).

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.

Skills

Computer Vision

Deep Learning

OpenCV

Python

PyTorch/TensorFlow

Docker

CI/CD

Edge AI

LLM integration

Education

Bachelor's or Master’s in CS/AI

Tools

ONNX

TensorRT

Jetson

Job description

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

• Strong 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