{"id":3612174,"url":"https://alion.io/job/apple-privacy-preserving-machine-learning-researcher-q","title":"Privacy-Preserving Machine Learning Researcher - Q","company":{"id":12,"name":"Apple","domain":"apple.com","url":"https://alion.io/company/apple","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Apple Jobs","truth_index":{"grade":"A","score":90,"open_postings":844,"ghost_share":0,"stale_share":0.188,"repost_share":0.002,"time_to_fill_p50_days":92,"computed_at":"2026-11-04T06:34:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Herzliya, Israel"],"countries":["IL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-11-02T12:44:34Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-04T10:34:43Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Our team is new, growing, and evolving quickly, and we are hiring across multiple disciplines. We work at the intersection of machine learning, hardware, and software, creating technologies that reshape how people communicate and experience the world around them in everyday life.\nDescription\nAt Apple, we believe privacy is a fundamental human right, and our research teams are dedicated to building technologies that deliver intelligent capabilities with rigorous, provable privacy guarantees.\nWe are looking for a research scientist with an extraordinary theoretical background in machine learning and computational mathematics. This is a foundational theory role: we are seeking someone who truly understands how learning algorithms function from first principles, identifies computational and statistical barriers, and proves what is achievable under information-theoretic constraints.\nWhile knowledge of privacy mechanisms (such as Differential Privacy) and cryptography is a strong advantage, the core priority is deep theoretical maturity in statistical learning, sample complexity, and optimization theory. You will bridge mathematical rigor with practical algorithmic innovation, shaping the next generation of private machine learning at Apple.\nMinimum Qualifications\nPh.D. in Computer Science, Applied Mathematics, Statistics, Electrical Engineering, or a related theoretical/quantitative field\nDeep theoretical foundation in statistical learning theory, computational complexity, and optimization (e.g., sample complexity, PAC learning, empirical process theory, or convex/non-convex optimization)\nProven track record of high-impact theoretical research and mathematical proof generation, demonstrated by publications in top-tier venues (e.g., COLT, NeurIPS, ICML, ICLR, STOC, FOCS, or IEEE TIT)\nStrong mathematical intuition and the ability to rigorously analyze the theoretical behavior and fundamental limits of algorithms\nHands-on ability to prototype, validate, and simulate algorithmic concepts using Python\nExcellent written and verbal communication skills in English, with the ability to convey complex mathematical theory to both theoretical peers and applied teams\nPreferred Qualifications\nDomain background or prior research in Differential Privacy (DP), DP-SGD, private PAC learning, or privacy budget accounting\nFamiliarity with cryptographic concepts and protocols (e.g., Secure Multi-Party Computation / MPC, Zero-Knowledge Proofs / ZKP, or Homomorphic Encryption)\nExperience bridging theoretical bounds with empirical deep learning models and large-scale training dynamics\nUnderstanding of information theory, concentration of measure, or high-dimensional statistics","description_format":"text","description_chars":2695,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"All 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