
Staff Machine Learning Engineer at Meta
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Experienced specialist in Machine learning, Natural language processing, Information Retrieval, Cloud Computing and Big Data infrastructures.
Université de Fribourg - Universität Freiburg
Doctor of Philosophy (Ph.D.), Computer Science
January 1, 2013 – January 1, 2017
Moscow Institute of Physics and Technology (State University) (MIPT)
Master’s Degree, Computer Science
January 1, 2009 – January 1, 2011
Petroleum Jobs
Master's degree, Chemistry
January 1, 2003 – January 1, 2008
Meta
Staff Machine Learning Engineer in Research (FAIR MSL)
May 1, 2023 – Present
Meta
Staff Machine Learning Engineer
July 1, 2020 – Present
Tesla
Senior Software Engineer
February 1, 2020 – July 1, 2020
Apple
Senior Machine Learning Engineer
July 1, 2017 – February 1, 2020
United States
Microsoft
Intern, Microsoft Research Silicon Valley
December 1, 2015 – July 1, 2016
Mountain View, CA
Yandex
Software engineer, Search Department
February 1, 2010 – August 1, 2013
Moscow, Moscow City, Russia
Oil and Gas digital library
Founding Member
January 1, 2005 – December 1, 2009
Ufa
Spring course in Information Design
Central Saint Martins, University of The Arts London
June 24, 2026 – Present
Pattern Discovery in Data Mining
Coursera
June 24, 2026 – Present
Data Visualization
Coursera Course Certificates
June 24, 2026 – Present
Natural language processing with Deep Learning
Stanford Engineering Center for Global & Online Education
June 24, 2026 – Present
Cloud Computing Concepts, Part 1
Coursera Course Certificates
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning research, machine learning, and software engineering across various prominent tech companies. While their experience is heavily skewed towards AI/ML and NLP, the target role of 'Big Data Engineer' aligns with their foundational skills in distributed systems and large-scale data processing. The breadth of their projects, from sentiment analysis to building compute platforms, indicates a versatile problem-solver. However, direct experience with specific Big Data technologies (e.g., advanced Spark optimization, Kafka, data warehousing) is not explicitly detailed beyond general mentions of Hadoop, Cassandra, and Spark in a research context, which might require some ramp-up for a dedicated Big Data role.
Soft Skills & Operational Fit
The candidate's resume indicates strong problem-solving skills and a research-oriented mindset, crucial for complex engineering challenges. Their experience at multiple leading tech companies suggests adaptability and a collaborative approach. However, specific details on stress handling or team collaboration are not explicitly provided in the assessment data.