Privacy-Preserving Machine Learning Researcher - Q
Core
Foundational theoretical research into the limits, bounds, and trade-offs of learning algorithms under privacy, computational, and statistical constraints.
Role type
Senior IC research scientist (theoretical machine learning & privacy)
Builds
Theoretical guarantees and novel privacy-preserving learning algorithms
Domain
Machine learning theory, differential privacy, computational mathematics
Deliverable
research
Required skills
statistical learning theory, computational complexity, optimization theory, mathematical proof generation, algorithm analysis, Python prototyping
Preferred skills
differential privacy (DP-SGD, private PAC), cryptography (MPC, ZKP, Homomorphic Encryption), information theory, high-dimensional statistics
Technologies
Python
Responsibilities
Formulate and prove theoretical guarantees for ML models; Design, analyze, and benchmark novel privacy-preserving learning algorithms; Author high-impact research papers in top-tier conferences; Collaborate with applied teams to translate theory into practical solutions
Seniority
Senior, hands-on IC
