CV

Full CV available upon request. You can contact me on LinkedIn or via email.

Brief

Versatile professional specializing in machine learning, applied mathematics, and NLP. Skilled in designing scalable ML solutions, managing complex projects, and mentoring teams.

Skills

Category Stack
Programming languages Python, C++, Javascript, Java, SQL
Machine Learning NLP, transformers, LLMs, Q/LoRA, RAG, RLHF, human-in-the-loop, synthetic data, LLM-Agents, PyTorch
Software Engineering web development, microservices (REST, gRPC), databases (PostgreSQL, MongoDB), FastAPI, SQLAlchemy, ASGI, model serving (vLLM, ONNX), CI/CD
Cloud & Infrastructure Microsoft Azure, Nebius Cloud, Docker/compose, Kubernetes, Helm, MLflow, AzureML

Experience

Toloka - Data for GenAI Company

Sr. Machine Learning Engineer (2024 - Present)

  • Led the development of AI tools assisting domain experts in faster and more accurate data labeling and production (e.g., automatic fact-checking).
  • Designed and implemented AI-generated content detection tools that filtered up to 80% of synthetic texts and code, ensuring high-quality datasets for LLM training.
  • Developed an automated LLM Red-Teaming pipeline that transformed policy descriptions into polished web reports detailing model safety and overdeflection rates. This reduced prototype creation time for LLM assessment cases to just a few days, enabling the sales team to showcase expected results more quickly and effectively.

Machine Learning Engineer (2022 - 2024)

  • Designed and implemented a multihead model architecture for content moderation (PyTorch, transformers, RoBERTa) across dozens of classes and languages. Built scalable data pipelines (including text augmentation techniques, e.g. GPT3Mix), reducing model development time for new classes/languages to < 3 days.
  • Designed and maintained production-grade ML web services that integrated automated NLP labeling with human oversight.
  • Contributed to the creation of an auto-ML library enabling easy training of classification models through endpoints (text/image). Collaborated on a dataset library offering unified interfaces for seamless data management.

RUDN University - Top 3 Russian universities according to the QS 2026 ranking

Software Engineer (2020 - 2021)

  • Led a development team to create multimedia-rich e-books (interactive websites) for the university.

Senior Lecturer (2020 - 2021)

  • Designed and launched new courses for undergraduates studying Computer Science and Business Informatics: Applied data analysis, Logical programming, and Enterprise IT infrastructure.
  • Published 10+ articles and conference papers in NLP and the use of machine learning methods in biomedicine.
  • Co-authored the MOOC ”Introduction to Marketing Analysis and Big Data,” which attracted over 5,000 online students. The course is now integrated into the university’s curriculum for Master’s-level marketing specialists.

Teaching Assistant (2014 - 2020)

  • Supervised research groups of four to six students. The commission marked the scientific works of three students as ”the best student work”.
  • Awarded as ”Favorite Teaching Assistant” based on voting among the students of the Faculty of Science.

Science and Technology Center ”IRM”

Software Engineer (2012 - 2013)

  • Gained software engineering experience by developing modules, optimizing databases, and authoring technical documentation (Java, SQL, Oracle Database).

Performance Lab - Leading enterprise software testing company

Software Test Engineer/Manager (2011 - 2012)

  • Streamlined testing processes with optimized SQL queries, reducing test time from 3 days to 6 hours, and trained three new Software Test Engineers.
  • Led teams of 2 to 5 engineers in conducting testing in production environments following releases.

Education

Articles and Publications

Comparative Analysis of Statistical Methods of Scientific Publications Classification in Medicine / Danilov, G.V., Zhukov, V.V., Kulikov, A.S. et al. // Computer Research and Modeling, 2020, vol. 12, no. 4, pp. 921-933

Approaches to Mathematical Model Development for Predicting the Transplanted Tumor Manifestation Speed in a Mouse Model of Human Breast Cancer / Aronov, D.A., Zhukov, V.V., Moiseeva, E.V. et al. // Sovremennye problemy nauki i obrazovania, 2020, no. 3

Imbalances in Cellular Immunological Parameters in Blood Predetermine Tumor Onset in a Natural Mouse Model of Breast Cancer / Aronov, D.A., Zhukov, V.V., Semushina, S.G. et al. // Cancer Immunol Immunother 68, 721–729 (2019)

Efficiency Analysis of the Word2Vec Modifications Compared to TF-IDF / Proshina, M.B., Zhukov, V.V.// ITTMM, Moscow, Russia, 2020

Quality Metrics Analysis of the Community’s Detection Algorithms in Social Networks / Kharitonova, A.S., Zhukov, V.V.// ITTMM, Moscow, Russia, 2019

Application of Support Vector Machine to Predict the Onset of Breast Cancer in Mouse Model / Zhukov, V.V., Aronov, D.A., Semushina, S.G. et al. // ITTMM, Moscow, Russia, 2018

Fun facts

I have a 1000-day streak on LeetCode (solving problems on C++).

I was selected for the Google FooBar challenge and successfully solved all tasks. Subsequently, I was interviewed by the Google team for a Software Engineer position. Unfortunately, I had limited practical experience at that time (2021).

I worked in a biomedical laboratory as a researcher.