Senior Staff Privacy Engineer

Quick Facts

• Senior, hands-on individual contributor privacy engineering role focused on AI products
• Own end-to-end privacy controls: detection/masking, privacy evaluations, and customer data use/retention/deletion

Description

AI products rely on sensitive data, so privacy must be enforced throughout collection, use, and protections across models, tools, logs, and pipelines. In this role, you will write production code and shape architecture for privacy controls, improving sensitive data detection and masking while assessing ML privacy risk. You will implement customer data-use and retention controls and run privacy evaluations as part of model and product releases.

Responsibilities

• Assess, benchmark, and select ML models and techniques meeting privacy requirements; build evaluation datasets and compare coverage, false positives, latency, cost, and product-quality impact
• Implement privacy models from prototype to production, including training/fine-tuning as needed, services/APIs, and inference performance and reliability optimization
• Build and deploy detection, masking, redaction, and tokenization for structured and unstructured data across logs, traces, APIs, analytics, and annotation tools
• Implement consistent masking/access controls and enforce customer data-use, access, retention, and deletion requirements across services and data stores
• Build privacy evaluations covering memorization, training-data extraction, membership inference, and sensitive disclosure via retrieval/tool use; implement mitigations and regression tests
• Prototype privacy-preserving evaluation approaches and synthetic data; measure privacy risk and utility and integrate solutions into ML pipelines
• Conduct privacy design reviews, identify gaps in data flows/architectures, and own or partner on code changes; build reusable components and standards
• Monitor privacy controls in production, investigate failures, improve detection quality, address regressions, and resolve customer-reported privacy issues

Requirements

• 7+ years building production software, including substantial privacy engineering and applied ML experience
• Strong Python with experience shipping production software; experience with Go, Java, C++, or another production systems language
• Hands-on ML model evaluation/selection/deployment experience (dataset curation, model adaptation/fine-tuning, error analysis, model serving)
• Experience building sensitive data detection and masking systems with accuracy/performance integration tradeoffs
• Experience assessing privacy risks in ML and LLM systems and implementing mitigations with clear test coverage and uncertainty understanding
• Deep understanding of data minimization, pseudonymization, anonymization, and re-identification risk
• Experience building data protection and lifecycle controls in distributed cloud systems
• Proven ability to take ambiguous problems from design through delivery and set technical direction/mentor engineers

Benefits

• Base pay: $201,300 - $352,300 plus equity (when applicable), variable/incentive compensation, and benefits
• Health plans including flexible spending accounts
• 401(k) plan with company match and ESPP
• Matching donations, flexible time away, and family leave programs