Evgeny Pavlov

LinkedIn, GitHub

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

Current AI projects

  • Firefox Translations (Mozilla) – efficient on-device Neural Machine Translation in a browser (this work is 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. Development of Firefox Translations web extension. (python, bash, C++, Slurm, Snakemake, JavaScript)
  • Firefox Addon Recommender (Mozilla) – 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)
  • Pocket recommendations (Mozilla)

Past AI projects

  • 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++)

Engineering

  • 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

  • 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

Education

Master’s Degree in Applied Mathematics

Courses

  • Natural Language Processing with Deep Learning (Stanford Center for Professional Development)
  • Deep Learning specialization (deeplearning.ai, Coursera)
  • Machine Learning (Stanford, Coursera)

Publications and talks

Hobbies

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