Nikola Jovanović
Member Of Technical Staff at Anthropic
Zurich, Zurich, Switzerland
Summary
👤
Senior🎓
Top SchoolNikola Jovanović is a machine learning researcher-engineer and final-year PhD student at ETH Zürich’s SRI Lab with 11 years of industry experience building production-ready ML and systems software. Currently a Member of Technical Staff at Anthropic, he has interned at Meta FAIR where he led the first watermark for autoregressive image generation and helped uncover novel watermark attacks (NeurIPS’25), and previously contributed ML and systems work at Snap, Improbable, and Google. His expertise spans trustworthy ML, generative-model robustness, geometry-aware AR systems, and efficient distributed data structures—combining a strong theoretical background with hands-on engineering. Nikola routinely bridges research and product: shipping prototypes that translate advanced papers into deployable features and compression algorithms for real client workloads. Based in Zurich, he pairs rigorous academic training with a penchant for practical, reproducible tooling that improves model integrity and system efficiency.
11 years of coding experience
BSc Computer Science, BSc Computer Science at Računarski fakultetHigh School Mathematics, Physics, Computer Science, High School Mathematics, Physics, Computer Science at Matematička gimnazija (Mathematical Grammar School)PhD Machine Learning, PhD Machine Learning at ETH Zürich
Serbian, English
Github Skills (41)
recurrent-neural-networks10
docker-image9
homomorphic-encryption9
graph-neural-network9
cpp8
encryption8
graph-convolutional-networks8
deep-learning8
cryptography8
pytorch8
geometric-deep-learning8
defense7
machine-learning7
python7
logistic-regression6
Programming languages (6)
Github contributions (5)
rand0musername/project-euler
Dec 2015 - Jan 2023
Contributions:14 pushes, 1 branch in 7 years 2 months
rand0musername/urnn
Nov 2018 - Dec 2021
Unitary Evolution Recurrent Neural Network
Contributions:4 commits, 26 pushes, 1 branch in 3 years 1 month
recurrent-neural-networksmachine-learningneural-networktensorflow
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