Airat Valiev
Lead Machine Learning Engineer @Voka 3d Anatomy & Pathology
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WORK HISTORY
Lead Machine Learning Engineer @Voka 3d Anatomy & Pathology
Munich, DE
Leading R&D for a cloud-native, AI-driven data warehouse for life-science and pharma R&D. My focus is on designing and building the production-grade Knowledge Base pipelines and agentic workflows that structure and analyze heterogeneous biomedical data.Agentic AI: Designing agentic workflows using LLMs for complex, domain-specific data analysis and reasoning for pharma use cases.NLP & KGs: Integrating specialized models (e.g, BioBERT) and Knowledge Graphs (KGs) to enable semantic data linking across molecular and clinical sources.MLOps: Deploying and benchmarking models in a production AWS environment (SageMaker, Bedrock, Glue, S3), focusing on rapid MVP-to-production cycles.
EDUCATION
Moscow Institute of Physics and Technology (State University) (MIPT)
Master of Science - MS, Technology leadership
Higher School of Economics
Doctor of Philosophy - PhD, ML
Moscow Institute of Physics and Technology (State University) (MIPT)
Bachelor's degree, Прикладная математика
Moscow Institute of Physics and Technology (State University) (MIPT)
Степень Магистра, Прикладная Математика
ABOUT AIRAT VALIEV
I am the expert who bridges the gap between complex science and valuable, shippable products.In my career, I\'ve seen countless brilliant scientific ideas fail to become viable products. My mission is to fix that. I translate deep scientific needs - from pharma R&D to clinical labs - into robust, production-grade AI systems that deliver tangible value.As an AI Engineer at Voka.ai, I currently contribute to a life-science data warehouse, building the scalable Knowledge Base pipelines and Agentic workflows that pharma companies need to accelerate discovery. This is a hands-on role, integrating everything from BioBERT and LLMs to Knowledge Graphs in a production AWS environment.This work is built on a foundation of \"idea-to-MVP\" experience. As the CTO & Co-Founder of SciWay, I led a product from initial concept, through pivoting and and customer interviews, to a deployed platform with paying pilot customers.My work is grounded in deep technical and scientific expertise, including:* AI for Drug Discovery: Developing multi-modal foundation models (nach0-pc) at Insilico Medicine.* Clinical AI: Building and deploying production NLP systems for personalized oncology at BostonGene.* Academic Research: A PhD (c) in Applied AI and top-tier publications at NeurIPS & ACL.I am always open to connecting with other product leaders, scientists, and engineers who are serious about building the next generation of tools for science.Core Expertise: Applied AI: Agentic LLM Workflows, RAG, VectorDB, NLP (Transformers, BioBERT) Biomedical Data: Knowledge Graphs, Ontologies (UMLS, MeSH), Multimodal biochemical data Product: User Discovery, MVP Development, Full-Stack Architecture Design Sci/Tech: Computational Chemistry, AWS, GCP, Kubernetes, Python, PyTorch
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