Astana, Kazakhstan
BSc of Robotics(NU 2015), currently Junior AI/ML engineer, Tomorrow School student, Network School member. Completing internship in Samruk Kazyna Ondeu as ML engineer.
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Astana, Kazakhstan
BSc of Robotics(NU 2015), currently Junior AI/ML engineer, Tomorrow School student, Network School member. Completing internship in Samruk Kazyna Ondeu as ML engineer.

Office, Astana · 1,300,000 to 1,500,000 KZT NET per month
TargetAI specializes in video analytics solutions. Responsibilities: • Design and develop CV/Video Analytics models: object detection (person, vehicle, face, etc.), tracking, recognition (face, license plates, attributes) • Work with video pipelines: RTSP/HTTP, decoding, frame sampling, batching • Adapt and customize models for real-world conditions: poor lighting, different camera angles, noise, compression, FPS drops • Fine-tune and retrain models for specific customer scenarios • Optimize inference for CPU • Reduce latency and resource consumption • Balance accuracy vs performance • Integrate ML models into production: backend services, edge devices, on-prem installations • Monitor model quality: precision/recall, data drift • Prepare and analyze datasets: annotation, validation, data augmentation • Build training and testing pipelines • Analyze model errors and quality degradation Requirements: • 4+ years of experience in Computer Vision/Video Analytics • Strong understanding of CNN, YOLO, SSD • Experience with PyTorch or TensorFlow, OpenCV, ONNX • Understanding of video formats and streams: RTSP, codecs (H.264/H.265), FPS, bitrate, latency • Experience in CPU-only inference optimization • Experience working with Linux • Deep understanding of OpenVINO • Knowledge of edge device logic • C++ for performance-critical parts • Kafka • gRPC/REST • MLOps skills: MLflow, model versioning, monitoring • Experience with large-scale CCTV projects

NeurIPS 2026 is coming, with the Competition Track featuring 16 competitions on various topics: • Scientific AI, Physics & Engineering: Learn2Design, Smart Buildings, Fusion Equilibrium, RealPDE, FAIR Universe Weak Lensing. • Healthcare/Bio: SimulacraBench, AMP Challenge, Speech Accessibility Project Challenge 2, Virtual Embryo. • Foundation Models, Reasoning & AI Evaluation: Steerability, Predictive AI Evaluation, AIMO Interpretability, QuantiPhy. • Robotics, Agents & Embodied AI: RoboSyn, RoCo-Spring, Agenthon for qunatitative finance Several more competitions will take place as part of workshops: EEG/EMG Foundation Challenge, AV Causal Reasoning Retrieval Challenge, Lean Refactor Arena, AgentOdyssey. Most competitions run in September and October. It is a great opportunity for anyone interested—including school students and people outside research—to tackle frontier problems faced by top labs, publish a paper about their solution, and attend the largest AI conference.
Faculty of Computer Science, HSE University, Moscow / ML Engineer at AIRA · Muscat
My research sits at the intersection of ML, LLMs and computer vision, with a focus on inference optimization (KV-cache compression, quantization) and ensemble methods for large-scale forecasting. In my recent paper (IJCISIM 2026, DOI: 10.70917/ijcisim-2026-4333) I showed analytically and empirically that geometric log-space ensembling is the MAPE-optimal aggregator for log-normal targets, reaching MAPE ≈ 4.77% on an 18,000-store retail forecasting challenge. Open directions: efficient LLM inference, vision-language models, and transferring multiplicative-error ensembling to new domains
I am looking for new opportunities
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NeurIPS 2026 will feature 16 competitions in scientific AI, healthcare, foundation models, robotics and other fields.
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Asel Yermekova compiled a structured collection of open Kazakh-language datasets for NLP, speech, and computer vision.
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Kazakhstan’s team won 2 gold, 2 silver and 4 bronze medals at IOAI. Dauzhan Beketov placed second overall.
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