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 key 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 & EvaluationThe 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 InternshipStipend: ₹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.

📌 AI/ML Research & Product Development Intern (India)
🏢 Code-X-Novas
📍 India