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About Me

MohammadMojtaba Roshani (mmRoshani)

I am an AI and distributed systems engineer focused on trustworthy machine learning, federated and decentralized training, and production-grade MLOps and LLMOps platforms. My work sits where research ideas meet the systems required to run them reliably.

I build across the full stack of modern AI delivery: distributed training and serving, agentic workflows, retrieval systems, streaming data platforms, and the observability, automation, and platform layers that keep models dependable after launch.

Alongside engineering, I teach, review, mentor, and write about AI engineering and data platforms. This site is where I share practical notes from building systems that need to be secure, scalable, and maintainable in the real world.

Trustworthy AIFederated LearningAgentic SystemsData PlatformsMLOps

AI, Agents & MLOps

  • Distributed training and serving
  • LLM systems and inference
  • Agent orchestration and tool use
  • RAG and vector retrieval
  • Experiment tracking and model lifecycle automation

Data & Streaming

  • Event-driven architectures
  • Stream and batch processing
  • CDC and real-time analytics
  • Operational data stores and search
  • Dashboards and observability

Platform Engineering

  • Python, TypeScript, Go
  • APIs and microservices
  • Linux, containers, and Kubernetes
  • CI/CD for ML and software systems
  • Technical leadership and delivery

Education

  • M.Sc. in Computer Software Engineering

    Shiraz University

    Distributed systems, federated learning, privacy-aware machine learning, and secure decentralized training.

  • B.Sc. in Computer Engineering

    Shahid Bahonar University

    Artificial intelligence, data mining, and applied machine learning.

Selected Highlights

  • Graduate research in privacy-aware federated learning and distributed coordination.
  • Hands-on delivery across MLOps platforms, streaming data systems, and agentic AI products.
  • Teaching, mentoring, and cross-functional technical leadership in research and industry settings.
  • Recognition in national academic, engineering, and applied AI competitions.
  • Professional certification in data engineering and platform-oriented software delivery.

Languages

Farsi (native)English (professional working proficiency)

Experience

  • AI Engineering

    Lead engineering for production AI products built around multi-agent workflows, retrieval-augmented reasoning, speech interfaces, and privacy-aware system design.

  • Platform Lead, Distributed AI

    Architect end-to-end machine learning operations platforms that automate training, evaluation, deployment, and monitoring for research and product teams.

  • Graduate Research Engineer

    Research and build distributed learning systems spanning federated, clustered, and decentralized training with privacy-preserving protocols and scalable orchestration.

  • Trustworthy AI Research Engineer

    Design secure collaborative learning approaches that combine encryption, privacy controls, and robust evaluation against common leakage and inference risks.

  • Research Engineer, Communication-Efficient ML

    Develop lightweight coordination methods for non-IID federated settings, including similarity-driven client grouping and neighbor selection without exposing raw model values.

  • Research Assistant & Platform Engineer

    Build distributed training and serving workflows, explore scalable LLM deployment patterns, and support research infrastructure for high-performance computing groups.

  • Software & Data Engineer

    Deliver large-scale streaming systems, access-control services, and cloud-native microservices for real-time operational data and IoT workloads.

  • Data Engineer

    Create automated ingestion and processing pipelines for analytics, geospatial monitoring, and high-volume behavioral data products.

Teaching & Seminars

Teaching assistant and seminar presenter on cloud computing, distributed systems, federated learning, secure machine learning, and real-time data processing.

Peer Review

Reviewer for workshops and conferences focused on trustworthy AI, AI safety, and socially responsible deployment.

Open Source & Writing

Contributor to open-source tooling and author of technical writing on AI engineering, data platforms, and production lessons learned.