
Timur Usmanov
Machine Learning Intern

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About me
Software Engineer @ Yandex | AWS Certified
Education

INHA University in Tashkent
2016 - 2020Bachelor's degree Computer Science and Software EngineeringGPA: 4.46 / 4.50, Top 1% of the Class, Dean's List
Experience

Periplus AG
Jun 2019 - Aug 2019Machine Learning InternParticipated in the internship program under the supervision of experienced mentors. Learned the basics of Artificial Intelligence, and Machine Learning specifically in Python (using Tensorflow/Keras, Pandas, Numpy, scikit-learn).

LDKR Group, Inha University
Feb 2020 - Feb 2021ResearhcerParticipated in a team to create an analogue of Princeton WordNet for further use by applications in Uzbek language:- Analyzed the structure of PWN and the source files- Performed data filtering and formatting of database files using Python- Used a lexical resource (dictionary) for automatic translation of PWN concepts- Optimized the time to query the database for faster structure traversal

"Single integrator - UZINFOCOM"โ LLC
Sept 2020 - Mar 2022Python Developer๐ ๐๐๐URL: https://myid.uz/en/Contribution:- Played a key role by developing an AI solution for biometric authentication to extend remote services portfolio of leading banks and marketplaces of Uzbekistan.- Researched the available liveness detection and face recognition AI models, built and trained (using Tensorflow) a liveness detection model that achieved a FPR of less than 2%.- To serve the models, created a service with FastAPI and Docker, and integrated the service with the rest of the idetification system. This allowed for automation of user verification allowing for significant cost reduction via employing less staff for manual application processing.- Developed new features for and maintained the main identification service in Django, improving user experience.๐ฃ๐ถ๐ถ๐บ๐ฎ๐๐Contribution:- Created an authentication service with Flask and Docker to enable face recognition in authentication flow for Presidential Schools, which allowed to engage 2 times less school staff during the entrance exam check-in process.- Sped up registration of school staff and applicants by creating a NoSQL (Apache Solr) database for vectors for fast face searching and flexible profile creation and modification.- Reduced the time to process creation of new profiles and check-ins by 2-3 times via utilizing capabilities of Tensorflow for AI model inference on multiple GPUs. Show less

EPAM Systems
Apr 2022 - Oct 2024Software Engineer๐๐ฎ๐๐ฎ ๐ฃ๐น๐ฎ๐๐ณ๐ผ๐ฟ๐บ ๐ผ๐ณ ๐ฎ ๐ฏ๐ถ๐ด ๐ ๐๐น๐๐ถ๐ป๐ฎ๐๐ถ๐ผ๐ป๐ฎ๐น ๐๐ป๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐ป๐ด๐น๐ผ๐บ๐ฒ๐ฟ๐ฎ๐๐ฒContribution:- Led the implementation of new features for part of the platform - broke down the requirements and collaborated with colleagues-experts in Snowflake, coordinated delivery of features, discussed potential design and integration with the frontend team.- Managed deployments, enforced good practices: code coverage of 90%, SOLID.- Created new serverless API using combination of API Gateway and Lambda functions, used Terraform configuration for IaaC management. The API allowed to automate management of isolated user spaces in Snowflake, eliminating the burden of processing user requests from experienced data engineers on the platform.- Improved user experience using optimizations for AWS Lambda functions. Maintained existing APIs in AWS environment (API Gateway, Lambda, RDS).๐ฆ๐ฒ๐ป๐๐ถ๐๐ถ๐๐ฒ ๐๐ป๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ถ๐ผ๐ป ๐๐ฒ๐ฎ๐ธ ๐๐ฒ๐๐ฒ๐ฐ๐๐ถ๐ผ๐ป ๐ฆ๐๐๐๐ฒ๐บ (๐๐ฃ๐๐ ๐๐ป๐๐ฒ๐ฟ๐ป๐ฎ๐น ๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐)Contribution:- Developed a service for leak detection automation (PII, access keys) in git repositories using FastAPI and Docker in AWS environment. Enhanced flexibility and scalability by refactoring the service into 3 separate ones, used SQS for communication.- Subscribed the service to Kinesis topic that was pushing commit events. Integrated the service with Github API for fetching commit information and code diffs, and employed an S3 bucket to store commit information in order to reduce calls to Github API for the repositories recurring in Kinesis messages.- Integrated the service with AI pipelines (SageMaker) to verify the potential leaks, which has lowered the number of false positive findings by more than 60%, which allowed for lesser utilization of humans for verification of the potential leaks. Show less

Yandex
Oct 2024 - nowSoftware Engineer
Licenses & Certifications
- View certificate
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AWS Certified Developer โ Associate
Amazon Web Services (AWS)Sept 2023
Languages
- enEnglish
- ruRussian
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