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Machine Learning Engineer & AI Developer




Language skills

English B2

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machine learning ML


Technology Information and Internet Information Technology & Services IT Services and IT Consulting

Professional Summary

Candidate is a seasoned Machine Learning Engineer with a strong background in the wireless industry, accumulating 5 years of expertise, showcasing a diverse skill set that spans various domains within the field of data science and artificial intelligence. Candidate brings a robust skill set encompassing Python, machine learning techniques, data science, statistical data analysis, data structures, computer vision, and natural language processing. With a proven track record in the wireless industry, the candidate is well-equipped to contribute to innovative solutions at the intersection of technology and data.

Video of Talent



National Academy of Sciences / PH.D. of Technical Sciences

2015 Sep - 2018 Jun

Yerevan, Armenia

National Academy of Sciences / Master's Degree at Informatics and Applied Mathematics

2013 Sep - 2015 Jun

Yerevan, Armenia

Yerevan State University / Informatics and Applied Mathematics

2009 Sep - 2013 Jun

Yerevan, Armenia

Certifications and Trainings


Senior Artificial Intelligence Engineer / Corpora

Full-time, Remote

Jun 2023 - Dec 2023 

Los Angeles, California, United States

  • Building AI legal assistant, using LLM's.

  • Solving real-world NLP problems from text classification to data extraction from documents.

  • Frameworks: Transformers, LangChain, OpenAI, Pinecone, FAISS, Chroma, LLamaIndex.

  • Skills: Generative AI · OpenAI Products · LangChain · Vector Databases

Machine Learning Engineer / Essential


2021 Mar - 2023 Apr

Yerevan, Armenia


Flexport (San Francisco, California) | Vaital (Bellevue, VA)

The project at Flexport involved mapping product descriptions to HS (Harmonized System) descriptions and codes using Natural Language Processing techniques. The main challenge was predicting the HS descriptions and their codes, which are subject to dynamic changes, based on various product descriptions.

The following tasks were performed:

  • Developed a multi-label classification model utilizing transformer-based models such as Bert, DistilBert, and Roberta to predict the unchangeable parts of the descriptions.

  • Conducted error analysis to identify areas for further improvement of the model.

  • Improved accuracy by incorporating techniques like Named Entity Recognition and Natural Language Inference.

  • Utilized large language models such as GPT-3 model to predict the dynamic parts of the HS descriptions.

  • Implemented an end-to-end pipeline using Flask API.

  • Deployed the pipeline on AWS using Amazon SageMaker and Docker containerization.


  • The roles involved in this project were Developer, Lead Machine Learning Engineer, and Mentorship of Junior and Mid-level team members.

Daimler Truck North America (Portland, OR) / Vaital (Bellevue, VA)

The project conducted at Daimler Truck North America focused on data analysis of truck behaviors to gain insights into how customers were utilizing their trucks. 

The main objectives of the project were:

  • Analyzing the average types of roads where drivers frequently traveled.

  • Analyzing the average speed of drivers.

  • Analyzing the electric and diesel prices across different regions.

  • Calculating the revenue when drivers transitioned between states during their journeys.

  • Visualizing the obtained results using tools like Tableau.

  • Roles/Responsibilities: The roles involved in this project were Developer and Data Analyst.

  • Language: Python

  • Environment: Databricks

  • Frameworks and Libraries: Pandas, PySpark, NumPy, SQL, OSRM.

Data Scientist / SmartClick.AI 


2018 Mar - 2021 Feb

Yerevan, Armenia

Worked on Machine Learning projects for tabular data and Computer Vision projects for both images and videos. Used frameworks Pandas, Numpy, Scikit-learn, PyTorch, Flask, TensorFlow and Keras.
One of my projects worked in SmartClick: License plate detection and character recognition. (Sphere - Computer Vision)


  • Language - Python.

  • Frameworks and libraries - OpenCV, YOLOv5, YOLACT, LPRNet, PyTorch, TensorFlow.

  • Collecting data of Armenian license plates.

  • Detect license plates of vehicles with YOLO.

  • Segment all characters on plates with YOLACT.

  • Recognize digits and letters with LPRNet and other models.


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