Ildar Salakhiev is a Machine Learning Engineer III based in London with 9 years' experience building production-grade NLP and voice assistant systems, and over 5 years focused specifically on advanced NLP, LLM fine-tuning and on-device model pipelines. He has driven product impact end-to-end—from dataset collection and GAN-based augmentation to quantization, evaluation and deployment—at companies including Mapbox and Meta, and led teams to grow chat and voice assistant coverage from zero to meaningful production metrics. Comfortable with both theory (dynamic programming, evolutionary and graph algorithms, clustering) and practice (PyTorch, AWS, SQL, Git, SCRUM), he has shipped and maintained large-scale codebases and open-source wake-word work. A habitual learner and competitor, he stays current via Andrew Ng courses, ArXiv/OpenAI research and frequent participation in Kaggle and hackathons, bringing a researcher’s curiosity to pragmatic engineering. Notably, he built a full on-device LLM pipeline and has experience operationalizing adversarial text GANs for robustness and weak-labeling tasks.
9 years of coding experience
7 years of employment as a software developer
Бакалавр, Mechatronics, Robotics, and Automation Engineering, 4,9, Бакалавр, Mechatronics, Robotics, and Automation Engineering, 4,9 at Московский Государственный Технический Университет им. Н.Э. Баумана (МГТУ)
Contributions:5 releases, 12 pushes, 1 branch in 2 years 10 months
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