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Domagoj Ćevid

Senior Machine Learning Engineer
Google DeepMind · Zurich, Switzerland · engineer
Gold Medal, IMO 2013 (Croatia) - Rank 10Gold Medal, IMO 2012 (Croatia)Silver Medal, IMO 2011 (Croatia)Silver Medals, IOI 2012 And 2013PhD Statistics, ETH Zurich (2021)Trading Intern, Jane Street London (2015)Data Scientist / ML Engineer, Google Zurich (2021-2024)ML Engineer, Google DeepMind (LLM Post-training)

Croatian mathematician and ML engineer; IMO 2012/2013 gold medalist and IOI 2012/2013 silver medalist. PhD in Statistics (ETH Zurich, 2021) on confounding adjustment/causal inference; BA and MMath in Mathematics from Cambridge. Data Scientist and machine-learning engineer at Google Zurich (2021-2024) working on Gemini/Bard, now on LLM post-training at Google DeepMind. Past summer trading internship at Jane Street, London (2015).

Domagoj Ćevid is a Croatian mathematician and machine-learning engineer. He won a silver medal at the International Mathematical Olympiad (IMO) 2011 and gold medals at IMO 2012 and 2013 competing for Croatia, and silver medals at the International Olympiad in Informatics (IOI) 2012 and 2013. He read mathematics at the University of Cambridge (BA 2013-2016, MMath 2016-2017) and completed a PhD in Statistics at ETH Zurich in 2021 under Peter Bühlmann (co-examiner Nicolai Meinshausen), with a thesis titled 'Confounding adjustment for causal inference'. He then worked at Google in Zurich as a Data Scientist (2021-2024) and as a machine-learning engineer on model tuning/quality for Gemini/Bard (2024), and is listed as a machine-learning engineer on LLM post-training at Google DeepMind. He held a summer trading internship at Jane Street in London in 2015.

Details
LocationZurich, Switzerland
Company sitedeepmind.com
UniversityETH Zurich
MathematicsProgrammingC++Problem SolvingPythonEnglishCLinuxComputer ScienceWindowsLeadershipGermanTeamworkTutoring
Notes
  • Quant employment verification: CONFIRMED for one quant-finance role. He held a Trading Intern role at Jane Street (London) in 2015 — Jane Street is a proprietary trading firm / market maker, so this is a genuine quantitative trading internship, not a student program. Evidence is a LinkedIn-derived index record (not independent primary-source confirmation). His current role is at Google DeepMind (technology, not finance). No other quantitative-finance employer is evidenced.2015
  • PhD in Statistics, ETH Zurich: oral doctoral exam passed 3 Sep 2021; thesis 'Confounding adjustment for causal inference'; examiner Prof. Peter Bühlmann, co-examiner Prof. Nicolai Meinshausen.Sep 3, 2021
  • IMO record (primary source, imo-official.org contestant 20718): gold 2013 (rank 10, 35/42), gold 2012 (rank 33, 28/42), silver 2011 (rank 113, 22/42), all representing Croatia.Jul 2013
  • Published research on deconfounding / high-dimensional inference (e.g. 'Spectral Deconfounding via Perturbed Sparse Linear Models', arXiv:1811.05352, with Bühlmann and Meinshausen; 'Doubly Debiased Lasso' in Annals of Statistics 2022). Academic email listed as [contact omitted].Aug 17, 2020
  • IOI record (stats.ioinformatics.org): silver medals at IOI 2012 (rank 40, 309/600) and IOI 2013 (rank 71, 383/600) for Croatia.Jul 2013
  • Co-authored a 2022 Bioinformatics paper 'Identifying cancer pathway dysregulations using differential causal effects' (applications of causal-inference methods to genomics).Mar 4, 2022
  • Oberwolfach (MFO) photo archive lists him as an Oberwolfach Leibniz Graduate Student (OWLG) at the 2019 workshop 'Statistical and Computational Aspects of Learning with Complex Structure'.2019
  • Competitive-programming handles: Codeforces 'dcevid', Topcoder 'dcevid'; ICPC World Finals 2014 participant (rank 54); listed in the Competitive Programming Hall of Fame.2014
  • Croatian media (Večernj́i list, 16 Jul 2012) covered him as a top Croatian mathematics student; the article reports background but is not an employment source.Jul 16, 2012
  • GitHub account 'dcevid' is associated with the name Domagoj Ćevid (github.com/dcevid).

Competition record

Croatia · IOI

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