AI/ML Research & Product Development Intern

AI/ML Intern – Research & Product
Company: Code-X-Novas
Role: AI/ML Intern – Research & Product
Department: AI/ML & Product Development
Work Mode: Remote
Duration: 45 Days
Structure: 15 Days Training & Evaluation + 30 Days Paid Internship
Stipend: ₹5,000 for the 30-day paid internship phase
Working Hours: 2-3 Hours/Day
Working Days: Monday–Saturday
Sunday: Off
Work Type: Flexible Remote
About Code-X-Novas
Code-X-Novas is a product and service-based technology company building scalable digital products and custom technology solutions for startups, businesses, and organizations.
From AI-powered products and automation to web, mobile, and enterprise solutions, we combine technology, product thinking, and innovation to solve real-world problems and create measurable impact.
Our Highlights
Among India’s Top 75 Emerging Startups – 2025
Represented India at the Dubai AI Festival
Delivered 100+ real-world projects across technology domains
Clients and collaborations across India, USA and Dubai
Building a growing portfolio of proprietary technology products
Products across AI, Education, Social Technology, Automation and more
Technology solutions reaching 700+ schools through associated educational networks
About the Role
We are looking for an AI/ML Intern – Research & Product who is interested in working beyond basic academic projects and wants practical exposure to AI/ML research, deep learning, experimentation, and product development.
You will work on research-oriented AI/ML problems and contribute to the complete development cycle:
Problem Understanding → Data Preparation → Research → Model Development → Experimentation → Evaluation → Optimization → Product Integration
The role provides exposure to areas such as:
Deep Learning
Computer Vision
Geospatial AI
Predictive Analytics
Research & Experimentation
Explainable AI
AI Product Development
Key Responsibilities
1. AI/ML & Deep Learning
Develop and experiment with Machine Learning and Deep Learning models.
Work with architectures such as CNNs, Transformers and Attention mechanisms.
Train, validate and optimize models.
Compare different approaches and architectures.
Analyze model performance and identify areas for improvement.
2. Data Processing & Analysis
Collect, clean and preprocess datasets.
Perform feature engineering and data analysis.
Work with structured, image-based and spatial datasets.
Build efficient data preprocessing workflows.
Handle datasets obtained from multiple sources and formats.
3. Computer Vision & Geospatial AI
Work with image and spatial datasets.
Explore computer vision-based prediction and classification problems.
Work with remote-sensing and geographical datasets where required.
Understand and implement AI approaches for spatial/geographical data.
Experiment with different approaches for real-world prediction problems.
4. Research & Experimentation
Read and understand relevant research papers.
Study existing AI/ML architectures and methodologies.
Implement selected research approaches practically.
Design and conduct experiments.
Evaluate different models using appropriate metrics.
Improve model accuracy, efficiency and scalability.
5. Explainable AI
Explore model interpretability techniques.
Work with approaches such as SHAP and feature importance analysis.
Analyze model behavior and understand important input features.
Help make AI predictions more interpretable.
6. AI Product Development
Convert AI/ML models into practical product features.
Collaborate with developers and product team members.
Support model/API integration into applications.
Test AI solutions against real-world use cases.
Optimize models for reliability and practical deployment.
Required Skills
Must Have
Strong understanding of Python
Fundamentals of Machine Learning & Deep Learning
Understanding of CNNs
Basic understanding of Transformers / Attention
Experience with PyTorch or TensorFlow
Understanding of data preprocessing and model evaluation
Ability to read and understand technical/research papers
Strong problem-solving and analytical skills
Willingness to learn and experiment independently
Good to Have
Computer Vision
Remote Sensing / Geospatial AI
GIS concepts
Satellite imagery
Raster data / GeoTIFF
Rasterio / GDAL
QGIS / ArcGIS
U-Net / ResUNet
SHAP / Explainable AI
FastAPI or model deployment
Previous AI/ML research or project experience
Who Can Apply?
B.Tech/B.E. students
Students from CSE, IT, AI/ML, Data Science, ECE or related branches
Candidates with strong AI/ML projects
Candidates who have implemented research papers or AI/ML architectures
Candidates interested in AI research and product development
Professional experience is not mandatory. Strong technical fundamentals and the ability to learn and implement matter more.
Internship Structure
Phase 1 — 15 Days Training & Evaluation
The first 15 days will focus on practical training, evaluation and understanding your technical capabilities.
You may work on:
AI/ML implementation tasks
Research-oriented assignments
Model development
Data preprocessing
Experimentation
Technical problem-solving
Research paper understanding
Evaluation Areas
Technical fundamentals
Learning ability
Problem-solving
Implementation skills
Research & analytical thinking
Task completion
Communication & collaboration
Consistency and commitment
Candidate who successfully complete the evaluation phase may continue to the paid internship
phase.
Phase 2 — 30 Days Paid Internship
Stipend: ₹5,000
During this phase, you will work on practical AI/ML and product-development responsibilities with greater ownership.
You will get exposure to:
Real-world AI/ML workflows
Model development and experimentation
Research implementation
Model evaluation and optimization
AI product integration
Collaboration with technical/product teams
Total Duration: 45 Days
15 Days Training & Evaluation + 30 Days Paid Internship
Continuation into the paid phase is based on performance during the evaluation period.
What You Will Gain
Hands-on AI/ML product development experience
Practical Deep Learning experience
Exposure to Computer Vision and Geospatial AI
Research-oriented AI/ML experience
Experience working with real-world datasets
Model experimentation and evaluation experience
Understanding of AI product development workflows
Experience collaborating with technical teams
Internship/experience certificate as applicable
Potential opportunity for continued association based on performance and available opportunities
Work Structure
Work Mode: Remote
Working Hours: 3 Hours/Day
Working Days: Monday–Saturday
Sunday: Off
Schedule: Flexible
Focus: Deliverables, learning and progress
Selection Process
Application → Screening → Technical Assessment → Technical Interview → Final Selection → 15-Day Training & Evaluation → Performance Review → 30-Day Paid Internship
Why Join Code-X-Novas?
You will get exposure to the complete AI development journey:
Research → Data → Model → Experimentation → Evaluation → Optimization → Product
You will work in a collaborative environment where learning, experimentation and practical implementation are valued.
How to Apply
If you are passionate about AI/ML, Deep Learning, Research and Product Development, we would love to hear from you.
Apply now and start building with Code-X-Novas.
Code-X-Novas — Build. Innovate. Scale.

Work arrangement
Yes