Mohammad Mahdi Mohajer mmohajer9

👨‍💻 Senior ML/Software Engineer @ LRQA

Engineer at ❤️ • 🔬 Researcher

Toronto, Canada 🇨🇦

_{* Also answers to Mo and Mamad. Yes, that explains the domain name.}

🧾 Abstract. This profile documents Mohammad Mahdi Mohajer, an engineer with dual expertise: a senior full-stack software engineer who became a senior machine learning engineer, with both skill sets kept sharp. He ships products from first commit to production and publishes peer-reviewed research on whether AI systems work as well as everyone claims. The condition is stable and productive.

🏷️ Index Terms: full-stack engineering · large language models · software testing · benchmarking · program analysis · production ML systems

1️⃣ Introduction

Most engineers ship AI systems. Most researchers doubt them. I do both, and I'm convinced neither works without the other.

I spent years as a senior full-stack software engineer before moving into machine learning, and I never put the first toolbox down. That mix is rarer than it should be: I can design the model itself 🧠 and also build the entire product around it, end to end 🏗️. My work spans production machine learning systems, the engineering that keeps them reliable, and research 🔬 on how to evaluate them honestly.

There are persistent founder symptoms too 🚀: ideas around me have a habit of turning into products. Figure 1 shows the loop that ties all of this together.

flowchart LR
    A(["💡 Spot an opportunity"]) --> B(["🏗️ Build the product"])
    B --> C(["🧠 Make it intelligent"])
    C --> D(["⚗️ Benchmark and test"])
    D --> E(["🚀 Ship to real users"])
    E --> F(["📄 Publish what holds up"])
    F --> A
    style A fill:#0099cc,stroke:#007aa3,color:#ffffff
    style B fill:#007fd6,stroke:#005bb8,color:#ffffff
    style C fill:#0057c2,stroke:#00459c,color:#ffffff
    style D fill:#3346c8,stroke:#2536a3,color:#ffffff
    style E fill:#5429b8,stroke:#41209c,color:#ffffff
    style F fill:#6b21a8,stroke:#581c87,color:#ffffff
    linkStyle default stroke:#0057c2,stroke-width:2px

_{Figure 1. Mohammad's operating loop, from opportunity to product to proof. No exit condition has been observed.}

2️⃣ Related Work

Mohammad's peer-reviewed work covers benchmarks for LLM coding ability, testing methods for deep learning libraries, and LLM-driven program analysis. The full record is archived in [3] 📚. His industry track record is documented separately in [2] 💼.

3️⃣ Apparatus: The Stack 🧰

📝 Programming Languages

🧠 Machine Learning

🖥️ Application Engineering

☁️ Infrastructure & Data

4️⃣ Threats to Validity

⚠️ This README was written by Mohammad himself, so take the self-report with a grain of salt. Don't trust the summary: read the papers [3] 📄, run the code 💻, or email him [5] ✉️ and draw your own conclusions.

References

#	Directory	Contents
[1]	🌐 mamad.ai	Mohammad's homepage
[2]	💼 LinkedIn	Industry track record, independently documented
[3]	📚 Google Scholar	Peer-reviewed publications, fully archived
[4]	🧩 Stack Overflow	Answers left in the wild
[5]	✉️ contact@mamad.ai	Correspondence. Hard problems preferred

📖 How to Cite

@misc{mohajer,
  author   = {Mohajer, Mohammad Mahdi},
  title    = {Full-Stack and Machine Learning Engineer: Ships the Whole Stack, Proves It Works},
  contact  = {contact@mamad.ai},
  url      = {https://mamad.ai},
  location = {Toronto, Canada},
  note     = {Responds faster to hard problems than easy ones.}
}

🙏 Acknowledgments

This research was supported by coffee ☕. Grants are accepted via:

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