Software Programmer (Neumann Team) Spring 2026 InternAt — M S International Inc.

As part of Curricular Practical Training, this internship will focus on advanced research and development projects that build upon prior work in Edge GPU-accelerated computing, secure network authentication, and natural language–based workflows. These projects are designed to strengthen the student’s understanding of mobile computing augmentation, real-time data processing, and secure infrastructure automation while contributing to MSI’s ongoing innovation initiatives.

Project 1: AI-Powered Inventory Intelligence on NVIDIA Jetson (GPU Edge Computing)

This project focuses on developing a real-time object oriented detection and reporting system running entirely on an NVIDIA Jetson Nano GPU platform using Raspeberry PI as a integrator to IOT on GPU.
The system uses:

• Computer vision models for object recognition and counting
• Modular Max / Mojo to accelerate inference on GPU
• Edge-based execution to enable real-time processing without reliance on cloud services

Outcome: Hands-on experience deploying AI workloads on GPU edge hardware, integrating computer vision, IoT to create a platform for developing a system which can perform automated inventory counts using computer vision.

 Project 2: Certificate Generation & Profile Provisioning (Secure Wi-Fi via EAP-TLS)

Certificate Generation and Profile Provisioning for Secure Wi-Fi Authentication
This project has been extended from past CPT experience. In this semester the focus is on developing a client application for automated certificate issuance using hardware-based root of trust where the application will generate a CSR from a secure enclave and generate CSRs. The student will learn to package the application on different Linux Systems  to automate the generation and provision of certificates to be used in IoT devices.

 Project 3: Real-Time Streaming Analytics Using Materialize + dbt Labs

This project introduces a real-time analytics and reporting system powered by:

• Materialize (streaming database engine)
• dbt Labs (data transformation and modeling framework)

Intern will create materialized views, build SQL transformation pipelines using dbt models, and integrate streaming data outputs with automated reporting.

Training:

The student will receive structured training across:
- MCP (Model Context Protocol) for natural language–driven data querying
- Modular Max for GPU acceleration (Jetson Nano + CUDA)
- dbt and Materialize for streaming data pipelines
- Certificate lifecycle automation and EAP-TLS provisioning

Mentorship will be provided by three members of the Neumann ITHW Operations Team: Myself, Preet Desai (Software Engineer), and Jeet Thakkar (Systems Engineer) through weekly reviews and open door discussion sessions will track progress and provide guidance.

Learning Outcome:

Upon completion, the student will gain hands-on experience in:
- Edge GPU computing
- Streaming data transformation and reporting pipelines
- PKI-based certificate management and secure authentication
- Real-world system integration, infrastructure automation, and enterprise software development
These projects reinforce core competencies in software and hardware engineering, cybersecurity, data engineering, and modern AI infrastructure deployment.