MoJa Ardestani

MoJa Ardestani

Applied Machine Learning Engineer with 4+ years of experience building NLP, Information Retrieval, LLM, and RAG systems. Skilled in developing production-oriented AI workflows, including conversational agents, retrieval pipelines, evaluation frameworks, and safety-focused model iteration for high-stakes domains.

About Me

Applied Machine Learning Engineer with 4+ years of experience building NLP, Information Retrieval, LLM, and RAG systems. Skilled in developing production-oriented AI workflows, including conversational agents, retrieval pipelines, evaluation frameworks, and safety-focused model iteration for high-stakes domains. Experienced in end-to-end AI system ownership, translating research prototypes into deployable LLM and RAG systems through data, modeling, evaluation, deployment, demos, and cross-functional collaboration with product, engineering, privacy, and research teams.

I have contributed to architecture design, technical scoping, and ML solution development across academic and industry projects. Beyond hands-on experimentation, I bring experience in cross-functional communication and stakeholder collaboration, with a strong emphasis on ethical deployment—including bias mitigation, factual consistency, explainability, and robustness. These experiences reflect my commitment to building principled AI and creating scalable, trustworthy systems for dynamic environments.

I completed my Master of Science in Computing Science at the University of Alberta, focusing on evaluation frameworks for LLM outputs, system design for Retrieval-Augmented Generation (RAG), and strategies for responsible GenAI deployment. I am passionate about advancing interpretable, reliable AI systems that align with human values and drive high-impact applications.

Education

University of Alberta

Edmonton, Canada

M.Sc. in Computing Science

Sept 2023 – Sept 2025

GPA: 4.0 / 4.0

Coursework

LLMs for Data Processing & Retrieval A
Introduction to NLP A+
Introduction to ML A
Knowledge Graphs A+

Publications

• "Do Nugget-Based Evaluation Patterns Generalize to List-QA?" - GEM @ ACL 2026

• "LongRecall: A Structured Approach for Robust Recall Evaluation in Long-Form Text" - Preprint

Amirkabir University of Technology

Tehran, Iran

B.Sc. in Computer Engineering

Major: Artificial Intelligence

2018 – 2022

GPA: 3.95 / 4.0

Selected Coursework

Data Mining A+
Information Retrieval A+
Artificial Intelligence A+
Principles of Computational Intelligence A+
Data Structures and Algorithms Design A+
Research and Technical Presentation A+

Thesis

"Design and Implementation of a Content-Based E-book Recommendation System"

Professional Experience

Machine Learning Engineer

My Viva Inc., Edmonton, Canada — Feb 2026 - Present
  • Developed an LLM-powered conversational AI system for personalized digital health and wellness support
  • Built AI pipelines for speech-to-text, conversation summarization, and user-profile integration
  • Designed retrieval-based memory components to improve chat continuity and recommendation relevance
  • Implemented evaluation workflows for response quality, safety, reliability, and privacy-sensitive use cases
  • Owned end-to-end delivery of AI features, from requirement scoping and prototyping to implementation, evaluation, demos, and production handoff

Machine Learning Resident

Amii, Edmonton, Canada — Oct 2025 - Feb 2026
  • Worked with Amii's Advanced Technology team to develop a personalized RAG-based assistant for a digital health platform
  • Improved document structuring, retrieval, and classification across a large wellness knowledge base
  • Built LLM components for personalization, guidance, and user-focused recommendations
  • Collaborated with product owners and engineers to deliver reliable AI features and demos
  • Improved model quality through iterative evaluation, focusing on safety, reliability, and user trust

AICAP WILO Participant

Amii, Edmonton, Canada — Jan 2024 - Oct 2025

AI Literacy – Content Development Support, Training Team (Aug 2025 - Oct 2025)

  • Supported development of educational content and training materials for AI literacy programs

AI Research Planning & Initiation (AIRPI), Advanced Technology Team (Jul 2025 - Sep 2025)

  • Designed and prototyped a RAG knowledge-base, enabling auto-refinement of retrieval results
  • Built and evaluated metadata classification pipelines to enhance retrieval across document formats
  • Collaborated with scientists and PMs in cross-functional teams to translate prototypes into deliverables
  • Developed feedback loops for automatic refinement and system improvement

Client Coaching – Startup Mentorship, Startup Team (Dec 2024 - May 2025)

  • Guided startup teams to architect scalable, cloud-deployable LLM/RAG systems with clear release paths
  • Advised on fine-tuning and retrieval strategies tailored to varied client data and constraints
  • Drove responsible AI deployment design, including bias mitigation and safe output generation
  • Translated complex ML strategies into actionable guidance for technical and non-technical stakeholders

Project Validation – Technical Advisement, Industry Team (Jan 2024 - Apr 2024)

  • Advised on designing an LLM-based pipeline for automated report generation using a RAG framework
  • Supported evaluation of factual accuracy, addressing hallucination and explainability
  • Recommended strategies for embedding fine-tuning to improve domain-specific retrieval

Data Scientist

Taaghche, Tehran, Iran — Apr 2021 - May 2023
  • Developed and deployed an advanced hybrid book recommendation system
  • Worked with large unstructured and multi-source text corpora to enable retrieval and evaluation at scale
  • Combined word embeddings with fine-tuned BERT + CNN, boosting recommendation relevance by ~20%
  • Applied SVR and KNN as fallback models to handle sparse user data, reducing false negatives by ~15%

Research Experience

Research Assistant

University of Alberta, Edmonton, Canada — Jan 2024 - Dec 2025
  • Built a fact-based recall evaluation pipeline for LLM outputs, enabling more reliable assessment
  • Achieved 10-40% F1 improvement over existing methods in generative QA
  • Developed a modular system combining fact extraction, candidate selection, and entailment checking
  • Scaled pipeline application across diverse domains, ensuring factual completeness and easy deployment

Research Intern

AGH University of Science and Technology, Krakow, Poland — Aug 2022 - Feb 2023
  • Worked on adaptation methods based on deep learning for incremental learning
  • Studied overfitting mitigation in incremental learning via custom adaptation and weighting strategies
  • Proposed dynamic backpropagation weights based on inverse cluster size via incremental clustering
  • Designed learning schemes tailored to changing data distributions in long-term tasks
  • Improved model generalization in evolving data environments through adaptive optimization

Research Intern

Institute for Research in Fundamental Sciences (IPM), Tehran, Iran — Aug 2020 - Feb 2021
  • Conducted fundamental research in mathematical modeling and computational methods
  • Applied advanced mathematical techniques to solve complex computational problems

Teaching Experience

Teaching Assistant

University of Alberta, Edmonton, Canada — Sep 2023 - Dec 2025

Supporting undergraduate and graduate students in computing science courses, providing guidance on assignments and projects.

  • Conducted office hours and tutorial sessions for various computing science courses
  • Graded assignments and provided detailed feedback on student work
  • Mentored students on research projects and final course projects
  • Assisted in developing course materials and practice problems

Instructor

Tehran Institute of Technology (MFT), Tehran, Iran — Jun 2019 - May 2023

Machine Learning Instructor (Mar 2021 - May 2023)

  • Designed and delivered comprehensive machine learning curriculum
  • Taught fundamental concepts including supervised and unsupervised learning
  • Guided students through hands-on projects and practical implementations
  • Provided mentorship on machine learning applications and best practices

Python Programming Instructor (May 2020 - May 2023)

  • Taught Python programming fundamentals and advanced concepts
  • Developed course materials and programming assignments
  • Guided students in building practical Python applications

C/C++ Programming Instructor (Jun 2019 - May 2021)

  • Introduced students to C/C++ programming language and computer science fundamentals
  • Taught memory management, data structures, and algorithm implementation in C
  • Designed hands-on labs and programming exercises

Teaching Assistant

Amirkabir University of Technology, Tehran, Iran — Sep 2019 - Feb 2023

Supporting undergraduate students in computer engineering courses.

Courses: Information Retrieval, Computer Architecture, Algorithm Design, Linear Algebra, Fundamentals of Computer Programming

  • Assisted professors in various computer engineering courses
  • Conducted laboratory sessions and provided technical support
  • Graded assignments and provided constructive feedback
  • Helped students understand complex technical concepts

Notable Projects

Triple and Event Extraction using Few-Shot & CoT Techniques

Enhanced LLMs for knowledge graph construction via prompt-based alignment for factual consistency. Developed an automated evaluation framework for scalable assessment of generated outputs.

LLMs Knowledge Graphs CoT Prompting

Explanation Generation for SQL Queries

Developed a system for generating explanations of SQL queries from natural language questions using Spider and BIRD datasets with LLMs to generate and evaluate SQL queries.

SQL Generation NLP LLMs

Medical Image Processing - COVID-19 Detection

Implemented COVID-19 Detection via Lung X-Ray Classification using DenseNet-121 for efficient transfer learning and feature extraction from medical images.

Computer Vision DenseNet Medical AI

Data Mining Projects Collection

Collection of data mining projects including Diabetes Risk Prediction with XGBoost, Neural Network Classifiers, Frequent Pattern Mining, and Cluster Analysis using DBSCAN & K-means.

XGBoost Deep Learning Clustering

Skills & Expertise

Core Expertise

LLM Evaluation RAG Systems Agentic LLMs ML System Design Knowledge Graphs

Machine Learning & Deep Learning

PyTorch TensorFlow scikit-learn Pandas

NLP & LLM Tooling

spaCy Hugging Face Transformers LangChain LangGraph LlamaIndex LangSmith

Vector Databases & Retrieval

FAISS Pinecone ChromaDB SQL Embedding-based Search

Programming Languages

Python C++ Java

MLOps & Infrastructure

Docker Kubernetes GitHub Actions AWS Google Cloud Azure

Leadership & Community

Director of External Relations & Partnerships

CSGSA, University of Alberta 2024 - 2025

Leading external partnerships and relationship building for the Computing Science Graduate Students' Association.

Director of Competitions & Events Committee

SSC, Amirkabir University of Technology 2020 - 2022

Managed and organized academic competitions, hackathons, and technical events for the Student Scientific Chapter.

Director of Scientific Committee

Amirkabir Artificial Intelligence Summit 2020 - 2023

Led the scientific committee for one of Iran's premier AI conferences, overseeing research presentations and technical content.

Honors & Awards

Alberta Graduate Excellence Scholarship (AGES)

University of Alberta — 2025

Awarded $12,000 CAD for outstanding academic achievement and research excellence. Learn more

Jeffrey R Sampson Memorial Award

University of Alberta — 2024

Awarded $1,800 CAD for exceptional academic performance and contribution to the department. Learn more

IAESTE-Nominated Research Intern

AGH University of Science and Technology — 2022

Selected for a competitive international research internship through IAESTE exchange program.

Outstanding Undergraduate Student

Amirkabir University of Technology — 2020

Recognized for exceptional academic performance and contributions to the department.

2nd Place - ICPC Programming League

Among 80 teams — 2019

Secured second place in a highly competitive programming competition with 80 participating teams.

Certifications & Professional Training

Responsible AI 2: Governance and Scaling for Leaders

Advanced training in AI governance, ethical scaling, and responsible deployment strategies for leadership roles.

Amii Jan 2026 Responsible AI

Responsible AI 1: Navigating Innovation in Practice

Practical foundations in responsible AI development, covering ethical considerations and innovation practices.

Amii Jan 2026 Responsible AI

Finetuning Large Language Models

Specialized training in fine-tuning techniques for large language models and transformers.

DeepLearning.AI Sep 2025 LLM

LangChain for LLM Application Development

Comprehensive course on building LLM applications using LangChain framework and LLMOps practices.

DeepLearning.AI Aug 2025 LangChain

Lab2Market Discover - Winter 2025 National Cohort

National cohort program focused on commercializing research and bringing innovative technologies to market.

Lab2Market May 2025 Commercialization

Applied AI Certificate

Comprehensive training in applied artificial intelligence techniques and real-world AI system deployment.

Amii Mar 2025 Applied AI

AI Professional Development Badge

Recognition for continued professional development in artificial intelligence practices and methodologies.

Amii Mar 2025 Professional Development

Work Integrated Learning Badge

Completion of work-integrated learning program combining academic knowledge with practical industry experience.

Amii Aug 2024 WIL

AI Career Exploration Badge

Exploration of AI career pathways and professional opportunities in the artificial intelligence field.

Amii Jul 2024 Career Development

Natural Language Processing with Classification and Vector Spaces

Foundational NLP course covering text classification, sentiment analysis, and vector space models.

Coursera Mar 2021 NLP

Data Science Orientation

Introduction to data science fundamentals, methodologies, and professional practices.

Coursera Mar 2021 Data Science

Mathematics for Machine Learning: PCA

Advanced mathematical foundations for machine learning, including linear algebra, multivariate calculus, and Principal Component Analysis.

Imperial College London Mathematics

Data Science Professional Certificate

Comprehensive data science training covering machine learning, data analysis, and statistical methods.

IBM Data Science