Machine Learning Developer
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.
ExperiencePython - 6 yearsMachine Learning - 6 yearsAmazon Web Services (AWS) - 3 yearsAmazon SageMaker - 3 yearsComputer Vision - 3 yearsDeep Learning - 3 yearsPyTorch - 3 yearsTensorFlow - 3 years
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.
Machine Learning Lead
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 (https://aws.amazon.com/partners/success/envoy-media-toptal/).
- 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.
Machine Learning Engineer and Consultant
- 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.
Head of Machine Learning
- 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.
Amazon SageMaker Consultant
Visably LLC (via TopTal)
- Provided consulting to the client to migrate their on-premise ML solution into Amazon SageMaker.
Machine Learning Engineer (Remote)
- 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.
- 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).
Developer of Recommender System (Freelance)
- Helped prototype a recommender system.
- Created, tested, and tuned a prototype with Python.
- Implemented the system within AWS infrastructure and made it production-ready.
- 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.
Head of Research and Education Center
- 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."
Digital Watermarking with Deep Learninghttps://github.com/ando-khachatryan/HiDDeN
Very Large Image Database with Advanced Search Functionality
Recommender System with Amazon SageMaker
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
PyTorch, NumPy, Keras, TensorFlow, SciPy, XGBoost, Scikit-learn, Pandas, OpenCV
Amazon SageMaker, PyCharm, Jupyter, Git, Visual Studio, TFS, AWS Fargate
Amazon Web Services (AWS), Jupyter Notebook, Visual Studio Code (VS Code), Docker
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), GPT, Generative Pre-trained Transformers (GPT)
Python, C#, SQL, C++, R, Python 3
Amazon S3 (AWS S3), Google Cloud
Ph.D. in Computer Science
Karlsruhe Institute of Technology - Karlsruhe, Germany
Master of Science Degree in Computer Science
Yerevan State University - Yerevan, Armenia
AWS Certified Machine Learning - Specialty
Amazon Web Services (AWS)
Deep Learning Specialization
Convolutional Neural Networks
Neural Networks and Deep Learning
Structuring Machine Learning Projects
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Graph Analytics for Big Data
Big Data Modeling and Management Systems
Machine Learning With Big Data
Big Data Integration and Processing