Machine Learning Engineer
CurrentBuilding LLM-powered applications, semantic search and RAG
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Anna Beketova is listed as Machine Learning Engineer at PermafrostAI, based in Vancouver, British Columbia, Canada. AeroLeads shows a matched LinkedIn profile for Anna Beketova.
Anna Beketova previously worked as Machine Learning Team Lead at Code For Bc and Machine Learning Engineer / MLOPs at Generative Ai And Traditional Ml Projects. Anna Beketova holds Master'S Degree In Data Science, Applied Mathematics And Computer Science, 9.2 from Higher School Of Economics.
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I'm a highly motivated and curious Machine Learning Engineer with wide experience in various ML tasks as well as Generative AI and building ML infrastructure; I'm eager to demonstrate my knowledge by solving real-world sophisticated tasks. Solving problems in:* Traditional Machine Learning (Real Estate Price Prediction, Clustering, Classification, Scoring)* Generative AI (OpenAI GPT4, ChatGPT, Anthropic Claude)* Computer Vision, Video Summarization* Social Network AnalysisMachine Learning with PyTorch, sklearn, XGBoost, SAS Demand-Driven Planning and Optimization.Data Visualisation with Matplotlib, Seaborn, Gephi, SAS VA, StreamlitLanguages: Python, SQL, R, JavaML/DL tools: Scikit-learn, PyTorch, gTTS, OpenAI GPT4 and Whisper, Pandas, NumPy, OpenCV, ONNX, moviepy, ffmpegBig data & DevOps tools: FastAPI, DVC, Git, Github Actions, Docker, MLflow, PySpark, Kubernetes,Cloud Technologies: AWS CDK, AWS Lambda, S3, EC2, IAM, API Gateway, DynamoDB, CloudFormation, AWS SageMakerDevOps practices: CI/CD, staging, logging, pre-commit hooks, linter, testing (pytest)As a fast learner, I'm eager to acquire new skills if needed. Now I'm currently in Vancouver, Canada, and legally authorized to work here so I'm looking for job opportunities as Machine Learning Engineer, Data Scientist, Machine Learning Operations Engineer (MLOPs Engineer).
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Vancouver, British Columbia, Canada
Building LLM-powered applications, semantic search and RAG
Vancouver, British Columbia, Canada
* Develop proof of concept (POC) to validate more than 16,000 Short-Term Rental listings and enhance enforcement of STR regulations, supporting British Columbia's housing affordability goals* Utilize the LLMs (Gemini 1.5, GPT-4o, etc) and Deep Learning techniques to extract features and analyze host reviews, rental descriptions and images* Collaborate cross-functionally with engineering, product management and AI teams
Vancouver, British Columbia, Canada
1) Currently building Legal ChatGPT to help Canadian lawyers find legal cases based on sophisticated criteria faster2) Insurance Claims Automation:* Developed a PoC that simplifies insurance form completion (both audio and text versions) for a Canadian insurance company with a customer base of over 2 million clients. The PoC aimed to decrease customer wait time from 3h to 1s during peak hours and reduce call center costs by 87%.* Designed a backend architecture utilizing AWS API Gateway and AWS Lambda, integrated with the OpenAI GPT-4 API, to create a robust and scalable system for processing and managing form automation.* Infrastructure as code with AWS CDK, gTTS for text-to-speech, and OpenAI Whisper for speech recognition.* MLOps practices: CI/CD, staging, logging, pre-commit hooks, linter.3) Hotel information Q&A:* Built a hotel information Q&A bot using OpenAI GPT-3.5, LangChain, and Chroma RAG, based on touristreviews and chat messages. Simplified the process of checking if a hotel satisfies unusual requests.4) Bank Transaction Fraud Detection:* Solved Binary Classification for an imbalanced dataset of over 1 million transactions and identity information. Performed feature engineering using PCA and label encoding, trained LightGBM* Built inference infrastructure using API Gateway to access the service, 3 Lambdas to add incoming requests to SQS, process them, store them in a DynamoDB table and return predictions. Implemented using AWS CDK* Conducted payload testing5) Real Estate Rentals Analytics:* Directed the end-to-end ML lifecycle for a rental price prediction project, including data scraping for over 50 cities in Canada, feature engineering, model development, and maintenance* Managed XGBoost, Linear Regression models with MLFlow, used Postgres Database
Vancouver, British Columbia, Canada
* Implemented end-to-end pipeline (Python 3, PyTorch) for preview generation (solved as Video Summarization task) * Researched 4 SOTA approaches (CA-SUM, PGL-SUM, DSNet anchor based and DSNet anchor free), reimplemented and reevaluated original papers, modified architectures to achieve better results* The international team was supervised by Senior Computer Vision Research Engineer* Technologies: PyTorch, OpenCV, Docker, ONNX, GPU, AWS, moviepy, ffmpeg* Source code: https://github.com/anya-mb/summarization_models_inference
Moscow, Russian Federation
Solving Text Analysis, Demand Prediction, Scoring, Optimization tasks for international companies.Python, SQL, SAS.• Developed pilot ML models to predict contractors’ default rates for one of the leading steel manufacturers in Russia. It was expected to help our customer to personalize contract conditions, decrease accounts receivable by 15%, increase revenue by 12%.• Built pilot ML models to predict sales for petcare department of one of the leading international FMCG companies. Decreased SMAPE by 16% and increased department efficiency.• Developed pilot algorithms for automatic parsing of company’ agreement documents in Russian (extracting companies’ related information, representative names and job titles, prices). The project was expected to reduce the company’s Annual Salary Costs by 9% and to facilitate the creation of a user-friendly platform for search and comparison of agreements by selected criteria.
Advanced Academic Scholarship and Diploma with Honours Master Thesis: "Instagram Hashtag Prediction using Sequential Analysis with Deep.
Full-time Machine Learning Engineer program. Courses passed: Advanced Python, Machine Learning, Natural Language Processing, Machine.
Bachelor Diploma: “Analysis of the Relationship Between Foreign Investment and Macroeconomic and Stock Market Indicators”. Time series.
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Anna Beketova works for PermafrostAI.
Anna Beketova is listed as Machine Learning Engineer at PermafrostAI.
Anna Beketova is based in Vancouver, British Columbia, Canada while working with PermafrostAI.
Anna Beketova has worked for Permafrostai, Code For Bc, Generative Ai And Traditional Ml Projects, Video Ai Assistant, and Business & Decision Group.
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Anna Beketova holds Master'S Degree In Data Science, Applied Mathematics And Computer Science, 9.2 from Higher School Of Economics.
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