Hybrid Algorithms Engineer, Differential Privacy

Posted 4 weeks ago

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About the role

  • Implement and analyse privacy loss accountants (RDP, zCDP) and their conversions to (ϵ, δ)-DP. Calibrate and apply noise mechanisms (Gaussian, Laplace) based on rigorous sensitivity analysis.
  • Develop algorithms for static and dynamic sensitivity analysis of relational operators. Build query rewriting logic to inject calibrated noise and manage a per-user privacy budget ledger.
  • Use Python AST manipulation and static analysis to enforce a DP-safe execution environment, ensuring user-submitted code cannot leak private information.
  • Implement and benchmark state-of-the-art algorithms (e.g., MWEM, PGM, PrivBayes variants) for high-dimensional synthetic data generation, analysing their privacy-utility trade-offs.

Requirements

  • Strong foundation in probability, statistics, and linear algebra. You must be comfortable with statistical modelling, proving bounds, and reasoning about error/variance.
  • Proficiency in Python for scientific computing, including numerical stability considerations (e.g., floating-point precision, clipping, scaling).
  • Demonstrated ability to translate mathematical concepts from academic papers or technical specifications into robust, well-tested code.
  • **Desirable**
  • Direct experience with differential privacy concepts or libraries (OpenDP, SmartNoise, TensorFlow Privacy).
  • Knowledge of compiler design, abstract syntax trees (ASTs), or program analysis.
  • Experience with machine learning, particularly with noise models, statistical learning theory, or generative models.
  • Familiarity with SQL parsers or database internals.

Benefits

  • Private Health Insurance
  • Paid Time Off
  • Work From Home, with one required in-office anchor week every six weeks for deep collaboration and planning
  • Training & Development

Job title

Algorithms Engineer, Differential Privacy

Job type

Experience level

Mid levelSenior

Salary

Not specified

Degree requirement

No Education Requirement

Location requirements

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