Max Losch is a Senior Machine Learning Scientist based in Berlin with 11 years of experience specializing in computer vision, model interpretability, and adversarial robustness. He transitioned from academic research—publishing in IJCV, ICLR, Cortex and GCPR during a PhD—to industry roles where he makes robustness and fairness testing practical for multi-modal, production-grade systems. At QuantPi he scaled model and dataset testing by introducing modular "Compositions", dataset pipelines, and concurrency improvements for image and video modalities. His work bridges rigorous subgroup-discovery research for trustworthy AI with hands-on engineering to make testing libraries easy to adopt and performant. Uncommonly for someone with a deep research background, he focuses on tooling and scalable pipelines that directly lower the barrier to robust ML evaluation in industry.
11 years of coding experience
3 years of employment as a software developer
Master of Science (M.Sc.), Machine Learning, Master of Science (M.Sc.), Machine Learning at KTH Royal Institute of Technology
Bachelor of Science (B.Sc.), Computer Science, Bachelor of Science (B.Sc.), Computer Science at Freie Universität Berlin
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Universität des Saarlandes
Contributions:5 commits, 10 pushes in 1 year 1 month
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.