Evgeny Pavlov

LinkedIn, GitHub

Hi, I’m Evgeny! Currently, I work at Mozilla as a Senior Machine Learning Engineer. My main area of interest is prototyping and deploying AI products in a full-stack manner – from Jupyter notebooks, ETL and training pipelines to scalable production services. I have experience shipping Deep Learning and Classical ML projects, including NLP/NLU, Machine Translation, Recommender Systems and Computer Vision in various companies. I’m based in Vancouver, Canada.

Current AI projects

  • Firefox Translations (2021 – Present, Mozilla) – efficient on-device Neural Machine Translation in a browser (this work was intially a part of the EU-funded project Bergamot). I developed a scalable end-to-end training pipeline in collaboration with researchers from the University of Edinburgh, configured training infrastructure and trained translation models for several languages. Participated in developement of Firefox Translations web extension. Currently leading the work on further scaling the training pipeline and improving quality of translations. (python, bash, C++, Slurm, GCP, Snakemake, Taskcluster, JavaScript)

Past AI projects

  • Pocket recommendations (Mozilla, 2022) – similar content and “For you” recommendations (Python, Gensim, Lightfm, Metaflow, AWS, Qdrant)
  • Firefox Addon Recommender (Mozilla, 2021) – recommends Firefox addons on Firefox Settings tab and AMO (related add-ons). Migration to GCP, maintenance, ETL pipelines, analytics (Python, GCP, scikit-learn, Spark, Airflow)
  • Press Reader Deep PDF (2020) – Deep Learning based segmentation and block classification for PDFs of newspapers and magazines (Pytorch, Kubeflow, GCP)
  • Press Reader recommender (2019) – Deep Learning news recommender (Tensorflow, Python, k8s, GCP)
  • Native AI recommender (2019) – Deep Learning based “Read more” recommender for third-party websites (Tensorflow, Python, k8s, GCP)
  • News360 recommender (2018) – personalized news feed. Deep Learning based recommender, training pipelines, training infrastructure, the subsystem for AB experiments (Tensorflow, Python, Airflow, k8s)
  • News360 NLP platform (2017) – designed and implemented microservices for extraction of topics and entities from news articles (batch processing, inference of NLP ML models, Python, XGBoost).
  • Cognitive Forms (2008-2011) – OCR for structured documents. I developed an algorithm for multi-field contextual recognition as my diploma project. (C++)


  • News360 (2016) – news crawler, analytics, migration of backend services from Windows C# stack to Python Linux stack using microservices architecture
  • Native AI analytics (2017) – monetization backend, analytics pipelines on Spark
  • NPTV (2013-2015) – C# framework for the development of interactive TV apps
  • Trud Expert (2011-2013) – desktop C# applicaiton on WPF

Pet projects

  • llm_sum – styled summarization with Large Language models
  • Attractions recommender – personalized recommendations of cool places to visit in British Columbia based on TripAdvisor reviews (Python, Pandas, Dask, Spacy, Gensim, ElasticSearch, React.js)
  • redhairtravel.com – travel blog on WordPress


Artificial Intelligence Program, Stanford, 2021-2023

Master’s Degree in Applied Mathematics, MISIS, 2006-2011


  • Natural Language Understanding (Stanford Center for Professional Development, cs224u, 2023)
  • Machine Learning with Graphs (Stanford Center for Professional Development, cs224w 2022)
  • Natural Language Processing with Deep Learning (Stanford Center for Professional Development, cs224n, 2021)
  • Deep Learning specialization (deeplearning.ai, Coursera, 2018)
  • Machine Learning (Stanford, Coursera, 2017)

Publications and talks


  • Music (electric guitar, drums)
  • Travelling (30+ countries)
  • Hiking, tennis, sailing and other random outdoor stuff