Martin is available for hire
Hire MartinMartin Mirakyan
Verified Expert in Engineering
Python Developer
Lisbon, Portugal
Toptal member since January 15, 2017
Bio
Martin has several years of experience in machine learning and full-stack development while working for companies like Meta, Picsart, and YerevaNN Research Lab. He specializes in full-stack web development and AI and has completed many projects in this field. Martin is an exceptional communicator—with frequent reachouts—and has experience working in all types of teams, from small (five members) to large companies like Facebook.
Portfolio
M37 Ltd
Machine Learning, Artificial Intelligence (AI), Prompt Engineering...
Profound Academy
Amazon Web Services (AWS), React, Next.js, Google Cloud, Firebase, Algolia...
Akomi
Python, Large Language Models (LLMs), Robotic Process Automation (RPA)...
Experience
- Python - 7 years
- Firebase - 6 years
- Artificial Intelligence (AI) - 6 years
- Machine Learning - 6 years
- React - 5 years
- Next.js - 3 years
- Large Language Models (LLMs) - 3 years
- PyTorch - 2 years
Work Experience
AI/LLM Back-end Engineer
2025 - 2026
M37 Ltd
- Helped create the MVP of the product to raise the initial seed capital.
- Developed an AI agentic workflow to perform deep research for a given publicly traded company.
- Created a scalable system that connects the back end to the front end without requiring the team to write a lot of backend-for-frontend code.
- Created an agentic orchestration layer that coordinated the work of several AI agents, including creating Excel files, generating podcasts and images, and performing deep analysis for a given company.
Technologies: Machine Learning, Artificial Intelligence (AI), Prompt Engineering, Large Language Models (LLMs), Financial Engineering, Quantitative Finance, Quantitative Modeling, Agentic AI, Agentic Frameworks, Fintech, Full-stack, AI Agents, Claude, OpenAI, OpenAI SDK, OpenAI API, MongoDB, LLM Agents, AI SDK, Claude Code, Claude Agent SDK, Pydantic, FastMCP, Docker, Amazon Web Services (AWS), AWS Cloud Development Kit (CDK), Retrieval-augmented Generation (RAG), AI Agent Orchestration, Model Context Protocol (MCP), Multi-agent Systems, Multi-agent Orchestration, RAG Pipelines, RAG Systems, Agentic RAG Systems, Generative Artificial Intelligence (GenAI), Architecture, Leadership, Technical Leadership, AI Engineering, Agentic Coding, WebSockets, Cursor AI, Codex, Software Engineering, Harness, AI Architecture, AI Consulting, AI Modeling, AI Product Strategy, Data Architecture, Product Strategy, API Integration
AI/Full-stack Developer
2021 - 2026
Profound Academy
- Developed an educational platform from scratch that provides learners with in-depth interactive computer science courses and an easy-to-use environment for tutors.
- Launched an AI assistant based on GPT models that helps students get unstuck faster, debug their code to find issues, and point out a direction to work on.
- Designed an end-to-end experience for tutors to create and maintain their courses. This includes course and exercise editors, statistics and monitoring, user access management, and supported content types.
- Created a live-coding real-time functionality that helps tutors answer students' questions faster and monitor their progress seamlessly.
- Created an automated grading system based on the OpenAI o1 series of models that helps teachers streamline the grading process of open-ended tasks like theorem proofs and essays.
- Implemented a cheating detection system that monitors the work done by students and detects if they're cheating - be it from an AI or another student.
- Created an end-to-end AI Agentic system to create and manage courses, which includes creating rich-text content, generating test cases, coordinating sub-agents, and working with interactive demos.
Technologies: Amazon Web Services (AWS), React, Next.js, Google Cloud, Firebase, Algolia, Neural Networks, Machine Learning, Python, TypeScript, Material UI, AWS Lambda, Google Cloud Functions, Generative Pre-trained Transformers (GPT), Amazon S3 (AWS S3), Amazon DynamoDB, Amazon EFS, Deep Learning, OpenAI GPT-4 API, Artificial Intelligence (AI), Vercel, Node.js, OpenAI o1, OpenAI API, OpenAI Gym, Claude, Stripe, Stripe API, Retrieval-augmented Generation (RAG), OpenAI, OpenAI SDK, Large Language Models (LLMs), Multistage LLM Chains, Prompt Engineering, Observability, Large Language Model Operations (LLMOps), Vector Databases, Bias Mitigation & Hallucination Reduction, Tools, Function Calling, Search Engine Optimization (SEO), Front-end Architecture, Server-side Rendering (SSR), Lazy Loading, APIs, Core Web Vitals, ECMAScript (ES6), REST APIs, Caching, Automation, AI Chatbots, Chatbots, Full-stack, Startups, CI/CD Pipelines, Serverless, Front-end, Google Cloud Platform (GCP), Open-source LLMs, Web Development, LangChain, Express.js, Data Visualization, SciPy, Full-stack Development, Pytest, AI Agents, Agentic AI, RAG Systems, Agentic RAG Systems, AI SDK, Claude Agent SDK, OpenAI APIs, Model Context Protocol (MCP), AI Agent Orchestration, Agentic AI Systems, Conversational AI, Multi-agent Systems, RAG Pipelines, Generative Artificial Intelligence (GenAI), Architecture, Education Technology (Edtech), Leadership, Technical Leadership, AI Engineering, Agentic Coding, WebSockets, AI-generated Video, Payment Gateways, Cursor AI, Codex, FFmpeg, Software Engineering, Harness, AI Architecture, AI Modeling, B2B, AI Product Strategy, Data Architecture, Business Strategy, Product Strategy, Web Applications, API Integration, User Interface (UI)
Senior Python Developer
2025 - 2025
Akomi
- Used Playwright and AgentQL to automate form-filling for several healthcare websites.
- Used MyPy and Ruff to organize the Python codebase.
- Introduced several improvements across the codebase to improve maintainability.
Technologies: Python, Large Language Models (LLMs), Robotic Process Automation (RPA), Automation, Selenium, Web Scraping, TypeScript, Next.js, OpenAI, Pydantic, AI Agents, Agentic AI, Playwright, AgentQL, Anthropic, Claude, Mypy, Refactoring, Celery, Asyncio, Ruff, Pytest, Poetry, Generative Artificial Intelligence (GenAI), Software Engineering, AI Consulting, B2B, Data Architecture, API Integration, Browser Automation
AI Engineer
2025 - 2025
FRAIM PTY LTD
- Used multiple AI service providers through LangChain to balance usage and costs.
- Restructured the AI service to use structured outputs to match the application's business logic.
- Updated the codebase to use the latest AI features from OpenAI and Anthropic.
Technologies: Python, LangChain, Machine Learning, Artificial Intelligence (AI), Large Language Models (LLMs), Vector Databases, Prompt Engineering, Retrieval-augmented Generation (RAG), LangSmith, Natural Language Processing (NLP), OpenAI, OpenAI API, Anthropic, Together.ai, Docker, FastAPI, PostgreSQL, Pgvector, OpenRouter, Mistral AI, Meta Llama, Generative Pre-trained Transformers (GPT), OpenAI GPT-4 API, SQLAlchemy, Python Asyncio, Asyncio, SQL, REST, RESTFul APIs, Agentic AI, Node.js, Pytest, Poetry, LangGraph, Generative Artificial Intelligence (GenAI), Transformers, Architecture, AI Engineering, Software Engineering, AI Architecture, AI Modeling, API Integration
Full-stack Developer
2023 - 2023
Endor Labs Limited
- Developed a full-stack app with Next.js (the App Router) and React (MUI). The app allows users to apply for jobs automatically using ChatGPT.
- Implemented a system using the ChatGPT API and Playwright. The system fills out online forms automatically and submits them.
- Used Algolia to index a large corpus of jobs to make them searchable.
- Implemented a resume-parsing system with PDF.js and the ChatGPT API to extract user-specific information that would be later used when filling out online forms.
Technologies: HTML, CSS, JavaScript, ChatGPT, OpenAI GPT-3 API, OpenAI GPT-4 API, Artificial Intelligence (AI), Web Scraping, Puppeteer, Playwright, Firebase, Vercel, React, Next.js, Streamlit, Firebase Cloud Functions, Algolia, CAPTCHA, Material UI, OpenAI Assistants API, OpenAI SDK, Large Language Models (LLMs), Multistage LLM Chains, Hugging Face, Hugging Face Transformers, Generative Pre-trained Transformers (GPT), Stripe, Prompt Engineering, Observability, Large Language Model Operations (LLMOps), Bias Mitigation & Hallucination Reduction, Function Calling, Tools, Front-end Architecture, APIs, ECMAScript (ES6), REST APIs, Caching, Automation, AI Chatbots, Chatbots, Data Scraping, Full-stack, AI Agents, Startups, CI/CD Pipelines, Serverless, Front-end, Google Cloud Platform (GCP), Open-source LLMs, Web Development, LangChain, Node.js, Express.js, Data Visualization, Full-stack Development, Generative Artificial Intelligence (GenAI), Architecture, Software Engineering, Data Architecture, Web Applications, API Integration, User Interface (UI)
AI Developer
2023 - 2023
Clark Alan Fish
- Implemented a ChatGPT API-powered app that would analyze different companies' privacy policies and answer users' questions about their privacy.
- Developed the app's front-end with Streamlit for quick iteration and to ship the MVP in several days.
- Implemented a summarizer based on ChatGPT that would parse the crawled text and summarize it into smaller chunks to ensure they fit in the GPT model's context length.
Technologies: Artificial Intelligence (AI), Machine Learning, AI Design, Python, Streamlit, OpenAI GPT-3 API, Generative Pre-trained Transformer 3 (GPT-3), Web Scraping, Selenium, Large Language Models (LLMs), OpenAI API, OpenAI SDK, Multistage LLM Chains, Prompt Engineering, Observability, Bias Mitigation & Hallucination Reduction, Tools, Function Calling, APIs, REST APIs, Caching, AI Chatbots, Chatbots, Data Scraping, Full-stack, CI/CD Pipelines, Serverless, Web Development, Data Visualization, Full-stack Development, Architecture, AI Engineering, Software Engineering, AI Architecture, Data Architecture, API Integration
Shipping App Developer
2021 - 2021
JM Agency Inc
- Implemented a custom shipping price estimation mechanism with Flask (Python) to improve the shipping price estimation in Canada.
- Developed a fully custom Admin UI to configure product and shipping discounts.
- Integrated the shipping estimations with Shopify through their API.
Technologies: Python, JavaScript, React, Flask, Firebase, Shopify, Shopify API, Shopify Plus, Front-end Architecture, APIs, ECMAScript (ES6), REST APIs, Automation, Full-stack, Google Cloud Platform (GCP), Web Development, Express.js, eCommerce, Full-stack Development, Django, Payment Gateways, Software Engineering, Web Applications, API Integration, User Interface (UI)
Natural Language Processing Expert
2020 - 2020
Omni
- Created and deployed a semantic search service built on top of solutions from MS-MARCO competition and Elasticsearch.
- Trained an extractive summarization based on BERT to facilitate the suggestion service.
- Helped deploy ML servicers with an automated CI/CD pipeline through GitHub Actions.
Technologies: Python, Flask, Elasticsearch, Docker, Docker Compose, Kubernetes, Amazon Web Services (AWS), TensorFlow, PyTorch, Machine Learning, Deep Learning, Git, Artificial Intelligence (AI), Observability, Fine-tuning, Large Language Model Operations (LLMOps), APIs, REST APIs, Caching, Automation, PostgreSQL, CI/CD Pipelines, Open-source LLMs, Data Science, Transformers, Architecture, Software Engineering, AI Modeling, API Integration
Software Engineering Intern
2019 - 2019
- Worked on an open-source project called Magma which aims to give network providers a mobile network core solution: Github.com/facebookincubator/magma.
- Created a command-line interface using the Python Fire library to expose some tool functionality.
- Used the Ryu SDN framework to dynamically add OpenFlow rules for test packets on the data-link layer.
- Tested packet tracing along with generating traffic with the Scapy library.
- Improved logging on the C/C++ level by migrating custom logging implementation to log. Some logs were lost with the previous implementation when the app service crashed.
- Experimented with the spdlog library to see if it's reasonable to migrate to spdlog in the future.
- Implemented all the services with gRPC and Protobufs. Added health-checking services to the tool. Used Open vSwitch with Wireshark to debug and trace the packets.
Technologies: Swagger, Protobuf, gRPC, C++, Python, Front-end Architecture, APIs, REST APIs, CI/CD Pipelines, Software Engineering, Data Architecture
Machine Learning Researcher
2017 - 2019
YerevaNN
- Participated in DIIN in Keras, the ICLR reproducibility challenge.
- Published a report on the reproducibility of a DIIN neural network architecture for natural language inference using Keras. The source code can be found in my projects.
- Handled the Keras implementation of the complex neural network called R-net designed by Microsoft Research for question answering (R-net in Keras).
- Published a blog post on the implementation details and reproducibility of the R-net paper.
- Completed my university capstone project: Word2morph2vec.
- Designed an end-to-end pipeline for extracting "linguistically accurate" morphological vectors for given words or sentences. Experiments were tested and evaluated on the Russian language.
- Developed a neural network for classifying relations of proteins in biological data.
- Architected a convolutional neural network with custom attention interaction and used a bidirectional recurrent neural network as a baseline.
- Used Keras or TensorFlow libraries for deep learning.
Technologies: Keras, TensorFlow, Python, PyTorch, Deep Learning, Machine Learning, Natural Language Processing (NLP), Computer Vision, Deep Neural Networks (DNNs), Artificial Intelligence (AI), Observability, Fine-tuning, Open-source LLMs, Machine Learning Algorithms, SciPy, Software Engineering, AI Modeling
Software Engineering Intern
2018 - 2018
- Worked on an internal tool for monitoring the viewability of advertisements (Ad measurement team).
- Used various front-end technologies such as React, Redux, and Flow (UI of the tool).
- Utilized the following back-end technologies: Hack (database queries and tool logic).
- Implemented machine learning using Python and FBLearner for predicting ad/viewability score.
- Presented the final tool in front of the New York, Seattle, and Menlo Park teams.
Technologies: Python, Hack, Flow, Redux, React, Machine Learning, Artificial Intelligence (AI), Front-end Architecture, APIs, REST APIs, PostgreSQL, Full-stack, CI/CD Pipelines, Front-end, Web Development, SQL, Data Science, Data Visualization, Full-stack Development, MySQL, React Redux, PHP, Software Engineering, Web Applications, User Interface (UI)
Android App Developer
2017 - 2017
Enoram
- Created several internal monitoring tools (Android apps).
- Implemented activity tracking on each internal project of the employees. We used an MVVM design pattern with an Android data-binding library in that project.
- Used RxJava/RxAndroid heavily for easy network request manipulation and fetching information from the database.
- Authenticated with Firebase, and most of the information was kept in the Firebase real-time database, which we used like a REST endpoint.
- Developed with a team several libraries which help deal with code easily in the MVVM world. One was creating and populating lists without adapters; just a list of the view models was enough.
Technologies: RxJava, Firebase, Android, APIs, Software Engineering
Machine Learning Engineer
2016 - 2017
PicsArt
- Implemented and trained different neural network architectures for image tagging (with Python/Caffe). All uploaded images have to be tagged to be searchable. We trained neural networks to do this work to automate this process with high accuracy.
- Built a C++ neural network library for providing low-level neuron-based operations instead of layer-based ones.
- Implemented a neural network for person segmentation (with Lua/Torch). Given an image, the network finds a person inside it and outputs a mask corresponding to that person.
- Developed a simple Android app for making tests on image captioning. When a user takes a photo, a neural network generates a sentence about that photo that is displayed to the user.
- Worked on a neural network responsible for mature content detection in pictures.
Technologies: TensorFlow, Caffe, Torch, Lua, C++, Python, Machine Learning, Computer Vision, Deep Learning, Neural Networks, Deep Neural Networks (DNNs), Artificial Intelligence (AI), Observability, Fine-tuning, APIs, REST APIs, Startups, CI/CD Pipelines, Data Science, Machine Learning Algorithms, Data Visualization, SciPy, Django, MySQL, FFmpeg, Software Engineering, AI Modeling, Data Architecture, API Integration
Project History
ABCDE: Approximating Betweenness-centrality Ranking with Progressive Drop Edge
https://github.com/MartinXPN/abcdeA graph neural network approach to approximate betweenness-centrality ranking in Graphs. Experiments on real-world and synthetic datasets show that our algorithm is faster in inference and requires several times fewer resources and time to train.
This work is submitted as a journal paper.
This work is submitted as a journal paper.
EPE-DARTS
https://github.com/MartinXPN/EPE-DARTSEPE-NAS with DARTS and for faster neural architecture search.
PyTorch Lightning implementation of differentiable neural architecture search with benchmarks on both DARTS search space and NasBench-201 search space. The approach is tested on several datasets, including CIFAR-10, CIFAR-100, MNIST, Fashion-MNIST, and Imagenet.
PyTorch Lightning implementation of differentiable neural architecture search with benchmarks on both DARTS search space and NasBench-201 search space. The approach is tested on several datasets, including CIFAR-10, CIFAR-100, MNIST, Fashion-MNIST, and Imagenet.
Neural Network Library
https://github.com/MartinXPN/NeuralNetworkThis library provides a low-level API to perform operations directly on neurons to utilize individual neurons in a neural network better. The current neural network library implementations are concentrated on layer-based operations.
YerevaNN Project Source Code and Additional Details
I published a report on the reproducibility of a DIIN neural network architecture for natural language inference using Keras. The code is open source and available on GitHub.
• https://github.com/YerevaNN/DIIN-in-Keras
I published a blog post on the implementation details and reproducibility of the R-net paper.
• http://yerevann.github.io/2017/08/25/challenges-of-reproducing-r-net-neural-network-using-keras/
• https://github.com/YerevaNN/R-Net-in-keras
I developed an end-to-end pipeline for extracting "linguistically accurate" morphological vectors for given words or sentences. The system is based on FastText and COMBO. Experiments are tested and evaluated in the Russian language.
Source Code:
• https://github.com/MartinXPN/word2morph
• https://github.com/MartinXPN/morph2vec
• https://github.com/MartinXPN/sentence2tags
• https://github.com/MartinXPN/word2morph2vec
• https://github.com/MartinXPN/ag-annotation
I architected a convolutional neural network with custom attention interaction and used a bidirectional recurrent neural network as a baseline.
Source Code
• https://github.com/YerevaNN/RelationClassification
• https://github.com/YerevaNN/DIIN-in-Keras
I published a blog post on the implementation details and reproducibility of the R-net paper.
• http://yerevann.github.io/2017/08/25/challenges-of-reproducing-r-net-neural-network-using-keras/
• https://github.com/YerevaNN/R-Net-in-keras
I developed an end-to-end pipeline for extracting "linguistically accurate" morphological vectors for given words or sentences. The system is based on FastText and COMBO. Experiments are tested and evaluated in the Russian language.
Source Code:
• https://github.com/MartinXPN/word2morph
• https://github.com/MartinXPN/morph2vec
• https://github.com/MartinXPN/sentence2tags
• https://github.com/MartinXPN/word2morph2vec
• https://github.com/MartinXPN/ag-annotation
I architected a convolutional neural network with custom attention interaction and used a bidirectional recurrent neural network as a baseline.
Source Code
• https://github.com/YerevaNN/RelationClassification
Image Coloring
https://github.com/MartinXPN/ImageColoringImage Coloring uses neural networks, and this implementation is a Wasserstein GAN for turning greyscale images into colorful ones.
Three Experiments:
• A simple approach: colorize a greyscale image in the lab space. Given the L channel as an input, predict AB channels.
• Classification: the AB space was divided into chunks of colors and treated as a classification problem.
• Wasserstein GAN: used generative adversarial networks to predict AB channels with both first and second approaches.
Three Experiments:
• A simple approach: colorize a greyscale image in the lab space. Given the L channel as an input, predict AB channels.
• Classification: the AB space was divided into chunks of colors and treated as a classification problem.
• Wasserstein GAN: used generative adversarial networks to predict AB channels with both first and second approaches.
Spell Checker
Spell Checker is an app designed for editing and correcting texts. The app works offline and supports several languages, including Armenian, English, and Russian. The app currently has more than 100,000 downloads.
Education
2019 - 2021
Master's Degree in Information and Language Processing Technology
Instituto Superior Técnico - Lisbon, Portugal
2015 - 2019
Bachelor's Degree in Computer Science
American University of Armenia - Yerevan, Armenia
Skills
Libraries/APIs
React, TensorFlow, Keras, PyTorch, PyTorch Lightning, Node.js, REST APIs, FFmpeg, RxJava, RxJava 2, Firebase Android SDK, Google Maps API, Picasso, Retrofit, ActiveAndroid, Natural Language Toolkit (NLTK), SpaCy, SciPy, Protobuf, PyTorch Geometric (PyG), Shopify API, Puppeteer, Playwright, OpenAI API, Stripe, Stripe API, OpenAI Assistants API, Hugging Face Transformers, SQLAlchemy, Python Asyncio, Asyncio, Pydantic, Mypy, React Redux
Tools
Pytest, Codex, PyCharm, Flow, IntelliJ IDEA, RxAndroid, Android Studio, Git, Travis CI, Jira, Docker Compose, Torchvision, WebStorm, Shopify Plus, ChatGPT, OpenAI o1, OpenAI Gym, Claude, Celery, AI SDK, Claude Code, Claude Agent SDK, AWS Cloud Development Kit (CDK)
Languages
Python, C++, Java, TypeScript, SQL, JavaScript, ECMAScript (ES6), Lua, Hack, HTML, CSS, PHP
Paradigms
App Development, B2B, Model View Controller (MVC), Model View ViewModel (MVVM), Automation, Search Engine Optimization (SEO), REST, Refactoring, Model Context Protocol (MCP)
Platforms
Firebase, Docker, Google Cloud Platform (GCP), Harness, MacOS, Android, Ubuntu, Kubernetes, Amazon Web Services (AWS), Algolia, AWS Lambda, Vercel, Shopify, LangSmith, Together.ai
Frameworks
Android SDK, Next.js, Express.js, Agentic Frameworks, Caffe, Redux, Swagger, React Native, Django, gRPC, Flask, Material UI, Streamlit, Selenium, FastMCP, LangGraph
Storage
NoSQL, PostgreSQL, SQLite, Elasticsearch, MySQL, Google Cloud, Amazon S3 (AWS S3), Amazon DynamoDB, Amazon EFS, MongoDB
Other
Machine Learning, Data Science, Artificial Intelligence (AI), Large Language Models (LLMs), Full-stack, AI Agents, Front-end, Agentic AI, RAG Systems, Architecture, AI Engineering, Software Engineering, Web Applications, Deep Learning, Retrieval-augmented Generation (RAG), Prompt Engineering, Observability, Fine-tuning, Large Language Model Operations (LLMOps), Vector Databases, Bias Mitigation & Hallucination Reduction, Front-end Architecture, Server-side Rendering (SSR), Lazy Loading, APIs, Caching, AI Chatbots, Chatbots, Startups, CI/CD Pipelines, Serverless, Open-source LLMs, Web Development, LangChain, Machine Learning Algorithms, Data Visualization, Full-stack Development, Function Calling, Tools, Transformers, Education Technology (Edtech), Agentic Coding, AI Architecture, AI Consulting, AI Modeling, AI Product Strategy, Data Architecture, Product Strategy, API Integration, User Interface (UI), Torch, Neural Networks, GitFlow, Natural Language Processing (NLP), Convolutional Neural Networks (CNNs), Graph Algorithms, Apps, Generative Pre-trained Transformers (GPT), Google Cloud Functions, OpenAI GPT-3 API, Generative Pre-trained Transformer 3 (GPT-3), OpenAI GPT-4 API, Computer Vision, Deep Neural Networks (DNNs), AI Design, Web Scraping, Firebase Cloud Functions, CAPTCHA, OpenAI, OpenAI SDK, Multistage LLM Chains, Hugging Face, Core Web Vitals, Data Scraping, Anthropic, FastAPI, Pgvector, OpenRouter, Mistral AI, Meta Llama, RESTFul APIs, eCommerce, Robotic Process Automation (RPA), AgentQL, Ruff, Poetry, Financial Engineering, Quantitative Finance, Quantitative Modeling, Fintech, LLM Agents, Agentic RAG Systems, OpenAI APIs, AI Agent Orchestration, Agentic AI Systems, Conversational AI, Multi-agent Systems, Multi-agent Orchestration, RAG Pipelines, Generative Artificial Intelligence (GenAI), Leadership, Technical Leadership, WebSockets, AI-generated Video, Payment Gateways, Cursor AI, Business Strategy, Browser Automation
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