Profile

Machine Learning & AI Engineer with 15+ years of R&D and production experience building AI and data-driven software systems. Experienced in designing production-grade Machine Learning (ML) and AI applications, backend services, event-driven data pipelines, and cloud-based solutions across text, structured, and time-series data. Strong background in Kafka, Kubernetes, Docker, Terraform, MLflow, LLMs, RAG, and AI agent development. Experienced with cloud services and Azure ecosystem, with a focus on translating ML capabilities into scalable and maintainable software systems. PhD in Computational Language Processing using ML Models, with five Microsoft Azure AI/data certifications.

Professional Experience

Machine Learning and MLOps Engineer

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

  • Designed and engineered a microservice-based platform for real-time time-series anomaly detection and clustering, deployed for major German utility and environmental organizations including StEB Köln, RWW, LANUK 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).
  • Designed and implemented processing workflows for both continuous streaming workloads and large-scale batch data processing, including hybrid orchestration of decoupled workloads.
  • Applied prompt engineering and fine-tuning, and deployed open-source LLMs locally to automatically interpret and summarize complex dashboard analytics.
  • Containerized and deployed production services on Kubernetes, using Helm for application packaging and Terraform for infrastructure provisioning.
  • Implemented ML lifecycle management and model tracking using MLflow.

Machine Learning Engineer

Snappfood (remote) | Oct 2023 – Feb 2025

  • Designed and developed an LLM-based conversational pipeline and intent-routing system for customer-support automation and CRM enhancement.
  • Built retrieval-augmented generation (RAG) pipelines for recommendation and query optimization, integrating retrieval and language-model components into application workflows.
  • Fine-tuned transformer models using domain-specific instruction datasets.

Machine Learning Scientist

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

  • Developed deep learning and transformer-based models for text analysis, including document classification, clustering, and structural modeling
  • Developed statistical and machine learning models for cross-domain text and image analysis
  • Analyzed long-range dependency modeling and temporal behavior in textual data

Machine Learning Scientist

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

  • Developed neural models for NLP, including generative AI, LSTM, Tree-LSTM, and end-to-end neural architectures
  • Implemented reinforcement learning approaches for neural NLP models
  • Researched and developed generative models for abstractive text summarization

Machine Learning Engineer / Team Lead

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

  • Led an Entity Recognition project as a core component of a Persian-language search engine, from proposal
  • preparation and planning through coordination and final delivery
  • Developed foundational machine learning and neural models for text analysis
  • Built and curated task-specific datasets for model development and evaluation

Machine Learning Engineer / Team Lead

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

  • Led the Text Processing Team and developed an NLP pipeline for large-scale news processing
  • Developed NLP components for named entity recognition, relation extraction, news clustering, and recommendation
  • Built an indexing and full-text search system, enriching indexed content with extracted linguistic and semantic information and optimizing search queries
  • Designed and curated task-specific datasets and developed machine learning models for multiple NLP tasks

NLP Developer & Data Scientist

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

  • Developed foundational language-processing modules for Persian
  • Analyzed linguistic corpora using statistical and machine learning models
  • Developed tools and algorithms for semi-supervised annotation of linguistic data

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

Machine Learning & Analytics

  • PyTorch
  • TensorFlow
  • scikit-learn
  • pandas
  • Matplotlib

AI & Agentic Systems

  • LLMs
  • AI Agents
  • Retrieval-Augmented Generation (RAG)
  • Vector & Semantic Search
  • LangChain
  • LangGraph
  • MCP
  • Hugging Face Transformers
  • Prompt Engineering

Data & Stream Engineering

  • Kafka
  • Kafka Streams
  • Apache Spark
  • PySpark
  • Airflow
  • Stream & Batch Processing

Backend & High-Scale Engineering

  • FastAPI
  • REST APIs
  • Microservices
  • Event-Driven Architecture

Cloud & Azure

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

MLOps & DevOps

  • Docker
  • Kubernetes
  • Helm
  • Terraform
  • GitHub Actions
  • MLflow

Programming Languages

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

Databases

  • PostgreSQL
  • MySQL
  • MongoDB
  • Chroma

Developer Tools

  • Git
  • Jupyter Notebook
  • Conda
  • Cursor
  • Claude Code

Teaching Experience

Lead Subject Matter Expert (SME)

Coursera / Hurix Digital, Online | 2026

  • Lead SME for the technical audit and validation of the Machine Learning Operations course, targeting the Microsoft AI-300: Machine Learning Operations Engineer Associate certification.

Teaching Assistant

University of Tehran, Tehran | 2016 – 2017

  • Machine Learning for Text and Language Processing

Lecturer

Behshahr University of Science and Technology, Behshahr | 2006 – 2007

  • Artificial Intelligence
  • Programming Languages I & II
  • Design and Analysis of Algorithms
  • Computer Graphics

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