Andranik Khachatryan, Developer in Yerevan, Armenia
Andranik is available for hire
Hire Andranik

Andranik Khachatryan

Verified Expert  in Engineering

Machine Learning Developer

Yerevan, Armenia
Toptal Member Since
June 3, 2019

Ando has an AWS Machine Learning Specialty certificate, a Ph.D. in computer science, and is passionate about machine learning. He specializes in "classical" machine learning, as well as computer vision with deep learning, and is constantly fascinated with GANs. He has experience deploying multiple ML products with Amazon SageMaker.


Envoy Media Group
Amazon Web Services (AWS), Python, Amazon SageMaker...
Things Inc.
Python 3, PyTorch, Jupyter, Jupyter Notebook, Google Colaboratory (Colab)...
Python, Amazon Web Services (AWS), PyTorch, Deep Neural Networks...




Preferred Environment

PyTorch, Python, Visual Studio Code (VS Code)

The most amazing...

...project has been creating an image search engine that would find the original from millions of candidates even if the query image was very heavily modified.

Work Experience

Machine Learning Lead

2019 - PRESENT
Envoy Media Group
  • Created an in-house framework that does auto-ML for data and tasks specific to Envoy Media Group. We used the AWS stack and could train and deploy a new model within an hour without writing code.
  • Contributed to feature our framework as a case study for Partner Success on AWS (
  • Trained, tested, deployed, and monitored machine learning models with Amazon SageMaker.
  • Collaborated with the Envoy Media Group team on their long-term AI/machine learning strategy.
  • Created a framework that supports easy model creation and lifecycle management, including monitoring and visualization. We have from 10s to 100s of live machine-learning models deployed in production.
Technologies: Amazon Web Services (AWS), Python, Amazon SageMaker, Artificial Intelligence (AI), Artificial Neural Networks (ANN), Gradient Boosted Trees, Data Science, Machine Learning, Docker, Jupyter Notebook, SciPy, XGBoost, Explainable Artificial Intelligence (XAI), Machine Learning Operations (MLOps), Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP)

Machine Learning Engineer and Consultant

2022 - 2022
Things Inc.
  • Trained our own diffusion models using various approaches. These models were done on Google Colab notebooks using weaker GPUs and smaller datasets, but we managed to get things working and were ready for large-scale experiments.
  • Investigated a large number of papers and codebases related to Denoising Diffusion Probabilistic Models (DDPM) and Denoising Diffusion Implicit Models (DDIM).
  • Did research on competitors, such as Midjourney, to understand where the industry stands at the moment.
Technologies: Python 3, PyTorch, Jupyter, Jupyter Notebook, Google Colaboratory (Colab), Computer Vision, Amazon Web Services (AWS), Amazon SageMaker, Generative Adversarial Networks (GANs), Diffusion Models, DDPM, DDIM, Image Processing

Head of Machine Learning

2020 - 2021
  • Developed the product matching engine prototype, which matched the same product from different sellers using their images and description. Used OpenCV and ConvNet-generated image features, as well as vector index storage and search.
  • Oversaw the long-term ML strategy for the company, deciding which directions are the most promising going into the future. Worked closely with other teams on the overall system architecture on AWS.
  • Supervised a small remote team tasked with bringing the product matching engine into production. By the time I left the company, we had a product matching API and an internally-developed labeling tool using the API.
Technologies: Python, Amazon Web Services (AWS), PyTorch, Deep Neural Networks, Artificial Neural Networks (ANN), Artificial Intelligence (AI), Computer Vision, OpenCV, TensorFlow, Deep Learning, FAISS, AWS Fargate, Amazon S3 (AWS S3), FastAPI, SQL, Image Processing, Jupyter Notebook

Amazon SageMaker Consultant

2019 - 2020
Visably LLC (via TopTal)
  • Provided consulting to the client to migrate their on-premise ML solution into Amazon SageMaker.
Technologies: Amazon Web Services (AWS), Amazon SageMaker, Jupyter Notebook

Machine Learning Engineer (Remote)

2019 - 2019
Pirate Labs
  • Created a recommender system delivering marketing emails for a company with multiple, diverse clients. Each client is a shop selling different products, and the shops are very different from one another. We created a single system that works for all.
  • Designed, implemented, and tested the recommender system. It was highly configurable and flexible, enabling it to effectively adapt to unique settings of each shop.
  • Oversaw the testing and helped with launching the system into production.
Technologies: Recommendation Systems, Factorization Machines, Python, Machine Learning, Data Science, NumPy, Pandas, SQL, Jupyter Notebook

Co-founder, CEO

2018 - 2019
NVision LLC
  • Created a cloud-based infrastructure for crawling, indexing, and supporting an image database of tens of millions of images.
  • Retrieved images from a database of tens of millions of images. Query images could be very heavily altered versions of the original.
  • Enabled digital watermarking of images (prototype).
Technologies: PyTorch, TensorFlow, Keras, OpenCV, Python, C++, SQL, Image Processing, Jupyter Notebook, Generative Adversarial Networks (GANs)

Developer of Recommender System (Freelance)

2017 - 2018
  • Helped prototype a recommender system.
  • Created, tested, and tuned a prototype with Python.
  • Implemented the system within AWS infrastructure and made it production-ready.
Technologies: Amazon Web Services (AWS), Git, Jupyter, NumPy, Python, SQL, Jupyter Notebook

Product Manager

2016 - 2017
  • Served as the product manager for an in-house developed ETL.
  • Participated in product creation from the start: design, implementation, testing.
  • Oversaw client deployments and service monitoring.
Technologies: TFS, R, Visual Studio, .NET, C#

Head of Research and Education Center

2012 - 2017
  • Created a highly demanded educational program with more than 10 applicants for one position.
  • Co-developed the overall strategy for the education center, including creating the curriculum, designing the admission process, and recruiting the lecturers. Managed 1-2 assistants who took care of day-to-day operations.
  • Managed entrance exams (up to three rounds) with more than 300 applicants and more than 20 lecturers/TAs/colleagues being involved in different rounds.
  • Researched and published in IEEE TKDE, currently ranked #1 by Google Scholar in the category "Databases and Information Systems."
Technologies: R

Digital Watermarking with Deep Learning
PyTorch implementation of paper "HiDDeN: Hiding Data With Deep Networks" by Jiren Zhu, Russell Kaplan, Justin Johnson, and Li Fei-Fei:

Very Large Image Database with Advanced Search Functionality

Image search database which indexes tens of millions of images and is able to find the original photo, even if query image is heavily cropped, resized, down-sampled, collage version of the original. Horizontally scalable, cloud-based.

Recommender System with Amazon SageMaker

Made a recommender system for a startup as a remote member of the team. The final implementation utilized Amazon SageMaker to train and deploy the model.

This was my first machine learning project, and it was fascinating. I started with a NumPy scratch-implementation and ended up using SageMaker, which had just been released at that time.

Machine Learning on Amazon SageMaker

Worked on model training, testing, deployment, monitoring, and re-training on Amazon SageMaker.
2007 - 2012

Ph.D. in Computer Science

Karlsruhe Institute of Technology - Karlsruhe, Germany

2003 - 2005

Master of Science Degree in Computer Science

Yerevan State University - Yerevan, Armenia


AWS Certified Machine Learning - Specialty

Amazon Web Services (AWS)


Sequence Models



Deep Learning Specialization



Convolutional Neural Networks



Neural Networks and Deep Learning



Structuring Machine Learning Projects



Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization



Machine Learning



Graph Analytics for Big Data



Big Data Modeling and Management Systems



Machine Learning With Big Data



Big Data Integration and Processing



PyTorch, NumPy, Keras, TensorFlow, SciPy, XGBoost, Scikit-learn, Pandas, OpenCV


Amazon SageMaker, PyCharm, Jupyter, Git, Visual Studio, TFS, AWS Fargate


Data Science


Amazon Web Services (AWS), Jupyter Notebook, Visual Studio Code (VS Code), Docker


Amazon S3 (AWS S3), Google Cloud


Python, C#, SQL, C++, R, Python 3




Game Theory, Deep Learning, Image Processing, Machine Learning, Artificial Intelligence (AI), Artificial Neural Networks (ANN), Neural Networks, Deep Neural Networks, Computer Vision, Economics, Recommendation Systems, Factorization Machines, Clustering, Data Analysis, Generative Adversarial Networks (GANs), Computer Science, FAISS, FastAPI, Gradient Boosted Trees, Microsoft Azure, Google Colaboratory (Colab), Diffusion Models, DDPM, DDIM, Explainable Artificial Intelligence (XAI), Machine Learning Operations (MLOps), Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT)

Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.


Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring