Fatemeh Rahimi

Senior Applied AI Scientist · NLP · LLM Systems

Fatemeh Rahimi

I build production NLP and GenAI systems with a focus on document understanding, retrieval, evaluation, and human-in-the-loop agentic workflows. Over the last 7+ years, I've shipped applied AI systems spanning transformer fine-tuning, RAG pipelines, and multi-agent LLM orchestration; most recently as a Senior NLP Scientist at Pythonic AI.

Featured Projects

Production and research highlights

Multi-agent Support Automation

Pythonic AI · 2025 – present

Architected an LLM-powered multi-agent support workflow to triage incoming requests, execute routine code and configuration changes, and escalate ambiguous cases to humans. Combined tool-using agents, retrieval, and human-in-the-loop review to reduce manual engineering effort and speed up support resolution.

PythonLLM APIssmolagentsHugging FaceRAGHuman-in-the-loopPrompt engineering

Production NLP Services

Pythonic AI · 2022 – present

Led development and deployment of 3 production NLP services for document understanding, serving real-world extraction and classification workflows. Acted as primary technical owner for one service and built evaluation pipelines to measure model quality across releases and support reliable iteration.

PythonPyTorchTransformersDockerREST APIsMLflow

Biomedical NLP Research

Imagia · 2020 – 2022

Researched and built NLP pipelines for clinical report analysis — including de-identification, named entity recognition, and measurement extraction. Applied transformer-based models (BioBERT, ClinicalBERT) to real-world hospital data.

PythonPyTorchspaCyBioBERTHugging FaceCLI tooling

MTLV: Multi-task Learning Library

Dalhousie University · 2020 – 2021

CLI library for exploring four multi-task learning architectures with pre-trained language models. Proposed a novel task-clustering approach that improved cross-task transfer. Published at ACM DocEng-2021; served as M.Sc. thesis.

PythonPyTorchBERTBioBERTBlueBERTHugging Face

Open Source

Contributions to public projects

Added four new tools to this MCP server for Microsoft 365 — create, create child, rename, and delete mail folders via the Microsoft Graph API. Closes a workflow gap where users couldn't set up destination folders before moving messages.

TypeScriptMicrosoft Graph APIMCPMail.ReadWrite

Work Experience

7+ years in NLP, AI, and production ML

Senior NLP Scientist

Feb 2022 – Present

Pythonic AI · Milwaukee, WI, US (Remote)

  • Led development and deployment of 3 production NLP services for document understanding; served as primary technical owner for one
  • Architected an LLM-powered multi-agent workflow with tool orchestration and human-in-the-loop escalation to automate support email triage and resolution
  • Built evaluation pipelines for LLM agents, measuring tool-calling correctness and workflow quality to support more reliable iteration across releases
  • Developed automation tooling to streamline internal workflows across data labeling, sprint planning, and QA
  • Coordinated cross-functional annotation workflows and mentored team members on NLP and applied AI best practices

Applied Research Scientist – NLP

Nov 2020 – Jan 2022

Imagia · Montreal, Canada (Remote)

  • Built NLP pipelines for hospital clinical report analysis — de-identification, named entity recognition, and measurement extraction
  • Applied and evaluated transformer-based models (BioBERT, ClinicalBERT) on real-world biomedical datasets
  • Designed production-grade CLI tools for end-to-end model inference on clinical documents

NLP Research Assistant

Mar 2019 – Apr 2021

Dalhousie University · Halifax, Canada

  • Applied and evaluated deep language models (BERT, BioBERT, BlueBERT) on downstream NLP tasks with rigorous experimental design
  • Developed MTLV — a multi-task learning library with 4 architectures and a novel task-clustering method (published at ACM DocEng-2021)

Data Analyst

Aug 2018 – Feb 2019

Ayten Company · Shiraz, Iran

  • Worked on social network analysis using Python, Neo4j, and MongoDB
  • Practised Scrum within an R&D software team

Skills

Core technologies and competencies

Languages

PythonSQL

LLMs & GenAI

Hugging Face TransformersRAG pipelinesLangChain / LangGraphOpenAI APIAnthropic APIMulti-agent orchestrationAgentic workflowsHuman-in-the-loop systemsPrompt engineeringLLM evaluation

ML / DL

PyTorchscikit-learnMLflowModel fine-tuning (PEFT / LoRA)

NLP

spaCyNLTKBERT / RoBERTa / ELECTRADocument understandingNamed entity recognitionText classification

Data & Experimentation

NumPypandasJupyterA/B testingStatistical analysis

Infrastructure

GitDockerREST APIsMLflowGitHub ActionsCLI toolingEvaluation pipelinestmux

Publications

Peer-reviewed research

MTLV: A Library for Building Multi-task Learning Architectures for NLP

Rahimi, F., Milios, E., Matwin, S.

DocEng 2021 — ACM Symposium on Document Engineering · 2021

Talks

Public talks and presentations

March 2025

Compound AI Systems

Explores the shift from thinking about AI as isolated models to understanding them as complex systems. Covers how system-level thinking enables smaller, more efficient AI that outperforms simplistic large-scale models — with a focus on safety, optimization, and real-world performance.

Compound AISystem designLLMsSafety

January 2025

Trends in LLM Collaboration — Debaters and Judges in Agentic AI Systems

Covers the latest trends in LLM collaboration, highlighting agentic AI systems. Explores how collaboration, debates, and LLM-as-a-judge techniques improve AI workflows, with practical strategies for real-world implementation.

Agentic AILLM collaborationMulti-agentProductivity

Education

Academic background

M.Sc. Computer Science

Dalhousie University · Halifax, Canada

GPA 4.07/4.3 · Thesis: MTLV multi-task learning library

May 2019 – April 2021

B.Sc. Software Engineering

Shiraz University · Shiraz, Iran

Senior project: Kitchen Safety IoT system

Sep 2013 – Feb 2018

Contact

Get in touch

© 2026 Fatemeh Rahimi