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Adam N. AI, Cloud and Machine Learning Platforms

My name is Adam N. and I have over 9 years of experience in the tech industry. I specialize in the following technologies: Python, OpenAI API, FastAPI, LangChain, PyTorch, etc.. I hold a degree in Bachelor of Science (BS), Master of Science (MS). Some of the notable projects I’ve worked on include: AI Integration at Munich startup, Anomaly Detection Pipeline for live IoT data. I am based in Ulm, Germany. I've successfully completed 2 projects while developing at Softaims.

I am a business-driven professional; my technical decisions are consistently guided by the principle of maximizing business value and achieving measurable ROI for the client. I view technical expertise as a tool for creating competitive advantages and solving commercial problems, not just as a technical exercise.

I actively participate in defining key performance indicators (KPIs) and ensuring that the features I build directly contribute to improving those metrics. My commitment to Softaims is to deliver solutions that are not only technically excellent but also strategically impactful.

I maintain a strong focus on the end-goal: delivering a product that solves a genuine market need. I am committed to a development cycle that is fast, focused, and aligned with the ultimate success of the client's business.

Main technologies

  • AI, Cloud and Machine Learning Platforms

    9 years

  • Python

    2 Years

  • OpenAI API

    7 Years

  • FastAPI

    3 Years

Additional skills

  • Python
  • OpenAI API
  • FastAPI
  • Langchain
  • PyTorch
  • Docker
  • DevOps Engineering
  • AWS Development
  • Machine Learning
  • Artificial Intelligence
  • Automated Workflow
  • REST API
  • Transformer Model
  • Natural Language Processing
  • Microsoft Power Automate

Direct hire

Potentially possible

Previous Company

SAP

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Experience Highlights

AI Integration at Munich startup

Implemented several AI workflows to automate business bottlenecks at a Munich-based startup for 6 months. Workflows ranged from recruiting and onboarding to marketing and offboarding.

Anomaly Detection Pipeline for live IoT data

Automated an ETL Pipeline which preprocesses raw IoT data, analyses it and notifies the user in case of anomaly. The Machine Learning Analysis was performed by computationally efficient Markov-Chain models customized for time series data.

Education

  • Universität Ulm

    Bachelor of Science (BS) in Computational Science and Engineering

  • Technische Universität Berlin

    Master of Science (MS) in Mathematics

Languages

  • Arabic
  • German
  • English