Lomonosov Moscow State University · Astana
Research on the latest methods for identifying preferences.
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Lomonosov Moscow State University · Astana
Research on the latest methods for identifying preferences.
Junior AI Engineer · Cloud Generis · Astana
I am a Big Data Analysis last-year student with hands-on experience in data analysis, machine learning, AI, and business automation. During my internship and current work at a technology company, I have worked with Bitrix24 and CRM data, built ETL pipelines and automated daily reporting, analyzed sales and customer data, and developed AI-powered tools for sales and business processes. I have also worked on machine learning and RAG projects using Python, including predictive modeling and LLM-based applications. My main interests are machine learning, statistical modeling, AI agents, and quantitative data analysis, with a particular interest in applying these skills to financial and risk-related problems.

DSML Reading Club Meeting #10 Speaker: Arystan Shokan Arystan Shokan earned a master's degree in mathematics from Boston University. His main research interests are in geometry and topology, including algebraic geometry, complex geometry, algebraic topology, differential geometry, and combinatorial geometry. Arystan also wrote a survey paper on Combinatorial Hodge Theory. At this meeting, Arystan will talk about Topological Data Analysis (TDA). In the seminar, we will explore how Topological Data Analysis can be used to study the shape and structure of data, especially when periodicity and cyclic states are present. We will discuss the key ideas of homology, Laplacians, and Betti numbers. Prerequisites: Linear Algebra 📅 Thursday, October 1, 12:00 KZ Time ➕ Add to calendar: https://calendar.app.google/rY4ghKSXMTBAQx186 ⚠️ Important about the meeting link: Only those who add it to their calendar will get access to the meeting—the Google Meet link will be inside.

Office · 1,300,000 to 1,500,000 KZT NET per month
TargetAI is focused on video analytics solutions. Responsibilities: • Designing and developing CV/Video Analytics models: object detection (person, vehicle, face, etc.), tracking, recognition (face, license plates, attributes) • Working with video pipelines: RTSP/HTTP - decoding, frame sampling, batching • Adapting and customizing models for real-world conditions: poor lighting, different camera angles, noise, compression, FPS drops • Fine-tuning and retraining models for specific customer scenarios • Optimizing inference for CPU • Reducing latency and resource consumption • Balancing accuracy vs performance • Integrating ML models into production: backend services, edge devices, on-prem installations • Monitoring model quality: precision/recall, data drift • Preparing and analyzing datasets: labeling, validation, data augmentation • Building training and testing pipelines • Analyzing model errors and quality degradation Requirements: • 4+ years experience in Computer Vision/Video Analytics • Strong understanding of CNN, YOLO, SSD • Experience with Face recognition pipelines • Knowledge of OCR/ALPR • Proficient in PyTorch or TensorFlow, OpenCV, ONNX • Understanding video formats and streams: RTSP, codecs (H.264/H.265), FPS, bitrate, latency • Experience optimizing CPU-only inference • Experience working with Linux • Deep understanding of OpenVINO • Knowledge of edge-device logic • C++ for performance-critical components • Experience with Kafka • Experience with gRPC/REST • MLOps skills: MLflow, model versioning, monitoring • Experience with large-scale CCTV projects
I am looking for new opportunities
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