Profile

ML/AI Engineer with 15+ years of R&D and production experience building machine learning systems across text, structured and time-series data. PhD in Computational Text Processing. Designs and ships large-scale, production-grade ML systems —NLP, LLM and time-series applications— on cloud platforms, backed by five Microsoft Azure AI/data certifications.

Professional Experience

ML Engineer

MOcons GmbH & Co. KG | Hochschule Ruhr West, Mülheim | Feb 2025 – Present

  • Designed and engineered a core backend microservice infrastructure for real-time time-series anomaly detection and clustering, deployed for major German utility and environmental organizations including StEB Köln, RWW, LANUV NRW, EGLV, and Bitcontrol.
  • Designed and implemented a Kafka / Kafka Streams event-driven streaming architecture processing up to 1,100 concurrent time-series streams with sampling frequencies from 1 to 15 minutes.
  • Built scalable pipelines for real-time ingestion, historical reprocessing, and long-term backfilling (up to 15 years of data).
  • Implemented ML lifecycle management and model tracking using MLflow.
  • Designed hybrid orchestration systems to manage decoupled streaming and batch data workloads.

ML Engineer & Data Scientist

Snappfood (remote) | Oct 2023 – Feb 2025

  • Developed intelligent conversational LLM pipeline and intent routing system for customer support automation and CRM enhancement.
  • Built retrieval-augmented generation (RAG) pipelines for recommendation and query optimization.
  • Fine-tuned transformer models using domain-specific instruction datasets.

ML Researcher and Developer

Friedrich-Schiller-Universität Jena, Jena | Jan 2019 – Sep 2023

  • Developed deep learning and transformer-based models for cross-domain text and image analysis, document classification, clustering, and structural modeling.
  • Conducted research in long-range dependency modeling and time-series behavior in textual data and built reproducible ML experimentation pipelines.

ML Researcher and Developer

Heidelberger Institut für Theoretische Studien, Heidelberg | Jan 2018 – Dec 2018

  • Designed LSTM and Tree-LSTM architectures for sequence modeling and generative models for abstractive summarization; applied reinforcement learning to neural sequence optimization.

ML Engineer / Team Lead

Intelligent Information Systems Lab, Tehran | Sep 2016 – Dec 2017

  • Developed a Java-based Named Entity Recognition (NER) system and supporting dataset as a core component of a Persian Search Engine.

ML Engineer / Team Lead

Mobin Information Technology Center, Tehran | Jan 2014 – Aug 2016

  • Built NLP pipelines for entity recognition and relation extraction; developed clustering and recommendation systems for large-scale news text data.

Computational Linguistics Developer

University of Tehran — NLP Lab, Tehran | May 2008 – Jan 2014

  • Developed foundational NLP modules and semi-supervised annotation frameworks for linguistic datasets.

Certifications

  • Microsoft Certified: Azure AI Engineer Associate (AI-102) | Azure AI Foundry, Azure OpenAI Service, Custom AI Agents, Azure AI Search, Document Intelligence
  • Microsoft Certified: Azure Developer Associate (AZ-204) | App Service, Azure Functions, Container Apps, Managed Identity, Event Hubs, CI/CD
  • Microsoft Certified: Azure Data Scientist Associate (DP-100) | Azure ML, MLflow, MLOps, AutoML
  • Microsoft Certified: Azure AI Fundamentals (AI-900) | Azure ML, Azure Vision, Azure AI Language, Azure AI Speech
  • Microsoft Certified: Azure Fundamentals (AZ-900) | VMs, Virtual Network, Microsoft Entra ID, Azure Policy
  • Astronomer Certification: Apache Airflow 3 Fundamentals | Workflow Orchestration, DAG Authoring, Scheduler, Operators/Sensors, Connections

Technical Skills

Programming Languages

  • Python
  • Java
  • C/C++
  • C#
  • R
  • MATLAB

Machine Learning & LLMs

  • PyTorch
  • TensorFlow
  • scikit-learn
  • Hugging Face Transformers
  • LangChain
  • LangGraph

Data & Streaming

  • Kafka
  • Spark
  • PySpark

MLOps & DevOps

  • MLflow
  • Docker
  • K8s
  • Terraform
  • Helm
  • GitHub Actions
  • Airflow

Azure

  • Azure ML
  • Azure AI Foundry
  • Azure OpenAI Service
  • Azure AI Search
  • Fabric

Development & Tooling

  • FastAPI
  • pandas
  • Matplotlib
  • Claude Code
  • Cursor
  • Conda
  • Git
  • Jupyter Notebook

Databases

  • Postgres
  • MySQL
  • MongoDB
  • Chroma

Selected Publications

  • M. Mohseni, C. Redies, and V. Gast, “Comparative analysis of preference in contemporary and earlier texts using entropy measures,” Entropy, Vol. 25, No. 3, 2023.
  • M. Mohseni, C. Redies, and V. Gast, “Approximate Entropy in canonical and non-canonical fiction,” Entropy, Vol. 24, No. 2, 2022.
  • M. Mohseni, V. Gast, and C. Redies, “Fractality and variability in canonical and non-canonical English fiction and in non-fictional texts,” Frontiers in Psychology, Vol. 12, p. 920, 2021.
  • C. Redies, M. Grebenkina, M. Mohseni, A. Kaduhm, and C. Dobel, “Global image properties predict ratings of affective pictures,” Frontiers in Psychology, Vol. 11, 2020.
  • M. Mohseni and A. Tebbifakhr, “MorphoBERT: A Persian NER system with BERT and morphological analysis,” in Workshop on NLP Solutions for Under-Resourced Languages co-located with ICNLSP, 2019 (top-performing system in the shared-task competition).

Other Interests

Financial Markets (Equities, Derivatives, Digital Assets) & Quantitative Finance • Cycling • Strength Training