AI Computer Vision Engineer — India Remote

AI Computer Vision Engineer — India Remote

Role Overview

We are looking for an experienced AI Computer Vision Engineer to join our project team and support the design, development, integration, and deployment of AI-powered computer vision solutions.

The ideal candidate will have strong hands-on experience in Computer Vision, Deep Learning, Python, image/video analytics, and AI model development, with the ability to take models from experimentation and prototyping through production deployment.

The role will involve developing computer vision models for image and video analytics, integrating AI solutions with enterprise applications, and optimizing model performance, scalability, and reliability for production environments.

Key Responsibilities

• Design, develop, train, and deploy Computer Vision and Deep Learning models for real-world business applications.
• Develop AI solutions for image and video analytics, including object detection, classification, segmentation, tracking, OCR, and related use cases.
• Build and optimize models using frameworks such as PyTorch and/or TensorFlow.
• Develop image and video processing pipelines using Python and OpenCV.
• Implement and fine-tune object detection models using YOLO, Faster R-CNN, and similar architectures.
• Develop solutions for image classification, semantic/instance segmentation, OCR, pose estimation, and facial analysis.
• Implement object tracking and video analytics using technologies such as ByteTrack and DeepSORT.
• Work with modern vision architectures, including Vision Transformers (ViT), Swin Transformer, SAM 2, and CLIP.
• Explore and implement Generative AI and synthetic-data techniques for computer vision model development and data augmentation.
• Integrate AI/Computer Vision models with enterprise applications, APIs, and production systems.
• Optimize model accuracy, inference performance, latency, memory utilization, and scalability.
• Prepare datasets, perform data preprocessing, augmentation, annotation analysis, and model evaluation.
• Troubleshoot model and deployment issues and continuously improve production performance.
• Collaborate with software engineers, AI/ML engineers, architects, and project stakeholders to deliver production-ready solutions.
• Document model architecture, technical implementation, performance metrics, and deployment processes.

Required Technical Skills

• 3–6 years of relevant experience in Computer Vision / AI / Deep Learning. Experience may be flexible based on the candidate's overall profile.
• Strong hands-on experience in Computer Vision and Deep Learning.
• Strong Python programming skills.
• Experience with OpenCV and image/video processing.
• Hands-on experience with YOLO and object detection frameworks.
• Strong experience with TensorFlow and/or PyTorch.
• Practical knowledge of:
• Object Detection
• Image Classification
• Image Segmentation
• OCR
• Object Tracking
• Video Analytics
• Understanding of model training, validation, evaluation, optimization, and deployment.
• Good understanding of computer vision algorithms, neural networks, CNNs, transformers, and deep learning concepts.

Preferred Technical Exposure

Candidates with experience in the following technologies will be strongly preferred:

Object Detection

• YOLO
• Faster R-CNN

Image Classification

• Vision Transformer (ViT)
• Swin Transformer

Pose Estimation

• YOLO Pose
• MediaPipe

Face Analysis

• FaceNet

Object Tracking

• ByteTrack
• DeepSORT

Action Recognition

• MoViNet
• I3D

Generative Vision & Data

• Synthetic dataset generation
• Data augmentation
• Synthetic data pipelines

Foundation Vision Models

• SAM 2
• CLIP

Vision-Language Models (VLMs)

• Hands-on experience with VLMs will be an added advantage.

Deployment & Infrastructure

Exposure to production deployment and MLOps practices is preferred, including

• Docker
• Kubernetes
• REST APIs / microservices
• Model serving and inference optimization
• Cloud-based AI/ML deployment
• GPU-based model inference
• CI/CD and production model deployment practices

Education

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electronics, Engineering, or a related technical discipline.

Equivalent practical experience with a strong Computer Vision portfolio will also be considered.

Location

India — Remote

Preferred Location: Noida / Delhi NCR

Candidates from other locations in India with strong relevant experience may also be considered.

Experience

3–6 years, flexible based on technical expertise, project experience, and overall candidate profile.

Ideal Candidate Profile

The ideal candidate is a hands-on Computer Vision Engineer who can work across the complete AI development lifecycle—from data preparation and model development to optimization, API integration, and production deployment.

Candidates with demonstrable experience building and deploying real-world Computer Vision applications, particularly involving image/video analytics and modern vision models, will be preferred.

Engagement

Employment Type: Project-Based / Contractual

Work Mode: Remote

Location: India

Preferred Location: Noida / Delhi NCR

Pay: ₹70,000.00 - ₹120,000.00 per month

Benefits

• Flexible schedule
• Work from home

Application Question(s)

• Your expected salary per month?
• Do you have strong hands-on Python experience?
• Which Deep Learning frameworks have you used professionally?

PyTorch

TensorFlow

Both PyTorch and TensorFlow

Other

• What is your hands-on experience with OpenCV?

No experience

Basic

Intermediate

Advanced

• Which object detection frameworks/models have you implemented in production?

YOLO

Faster R-CNN

SSD

Other

None

• Which of the following Computer Vision tasks have you worked on professionally?

Select all that apply.

Object Detection

Image Classification

Image Segmentation

OCR

Object Tracking

Pose Estimation

Face Analysis

Action Recognition

Video Analytics

• Which object tracking technologies have you worked with?

ByteTrack

DeepSORT

SORT

Other

None

• Have you worked with Vision Transformers or transformer-based vision models?

Yes — ViT

Yes — Swin Transformer

Both

Other

No

• What experience do you have with OCR solutions?

Production implementation

Project/prototype implementation

Basic exposure

No experience

• Do you have experience with Vision-Language Models (VLMs)?

Yes — production

Yes — project/prototype

Basic exposure

No

• Have you integrated Computer Vision/AI models with enterprise applications or APIs?

Yes — extensively

Yes — some experience

Basic exposure

No

• Please describe one Computer Vision project you personally developed and deployed. Include the problem statement, model/technology used, dataset, your specific contribution, and production outcome.

Experience

• Computer Vision / Deep Learning: 3 years (Required)

Work Location: Hybrid remote in Noida, Uttar Pradesh (Noida)