Applied AI & Machine Learning Fellowship
Work alongside research engineers building computer vision pipelines, retrieval-augmented generation systems, and edge neural inference models.
About the Engineering Track
This program is an immersive, project-centric engineering fellowship. Interns build production-ready machine learning workflows rather than toy notebook exercises. You will gain hands-on experience handling real datasets, model quantization, API serving, and performance benchmarking.
Production Systems & Scope of Work
- Data ingestion, cleaning, and augmentation pipelines for image and tabular data
- Fine-tuning and evaluating vision and transformer architectures
- Model quantization (FP16/INT8) and inference optimization using ONNX Runtime
- Building high-throughput FastAPI REST endpoints for real-time model inference
- Dockerizing model workloads and deploying to edge and cloud instances
Skills & Architectural Paradigms Mastered
Eligibility Requirements
- Pursuing or completed B.Tech, M.Tech, BCA, MCA, or related degree in Computer Science, Data Science, or Engineering
- Proficiency in Python and basic understanding of linear algebra and calculus
- Familiarity with Git and version control workflows
- Strong problem-solving curiosity and enthusiasm for hands-on systems programming
Technologies Practiced
Progression Roadmap
Program Structure & Phases
A structured engineering progression taking you from foundational architecture to verified production delivery.
Foundations & Data Engineering
Deep dive into model architectures, vector embeddings, and rigorous data preparation standards.
Core Model Engineering & Training
Training, evaluation, hyperparameter tuning, and model validation with benchmark tracking.
Inference Engine & Microservices
Packaging models into Docker containers, building FastAPI microservices, and testing edge inference.
Production Hardening & Capstone Showcase
Latency optimization, documentation, code review, and final presentation to engineering leadership.
Fellowship Returns
What You Gain as an Engineering Fellow
Our mentorship model is built to ensure your deliverables create undeniable career leverage.
Direct 1-on-1 mentorship with senior engineering and research staff
Production-grade code contributions for your GitHub portfolio
Official NEELAXI Internship Certificate & Performance Letter
Potential pre-placement offer (PPO) for standout performers
Inquiries
Frequently Asked Questions
Details on eligibility, academic NOC compatibility, and stipend structures.
Yes, NEELAXI provides a merit-based monthly stipend to all selected engineering fellows.
Ready to Build Production-Grade Systems?
Fellowship cohorts fill on a rolling evaluation schedule. Submit your credentials to be considered for our technical review board.