Maxim Nikolaev is a Machine Learning Engineer with 8 years of experience translating research into production-grade ML systems, currently working on recommendation systems at VK. He specializes in generative computer vision, diffusion models, GANs, LLMs and ASR, and pairs deep modeling expertise (PyTorch, Diffusers, Transformers) with MLOps and performance optimization (Spark, Docker, gRPC, Prometheus, AWS). Across roles at AIRI, Yandex and HSE he has taken several prototypes through to user-facing deployments, bridging academic research and product constraints. He’s completing graduate studies in modern computer science and frequently operates at the intersection of research and engineering—comfortable tuning diffusion pipelines as well as building the infra to serve them at scale. Based in Moscow and open to senior roles, he combines hands-on model development with pragmatic observability and scaling practices.
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Contributions:2 releases, 9 commits, 6 PRs in 10 months
pythonregular-expressionyandexbeautifulsoupsaver
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