We are posting this job on behalf of our client.

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

Robust 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

Responsibilities:

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

📌 Machine Learning Engineer (Kochi)
🏢 Filuet
📍 Kochi