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Differential Privacy Jobs (NOW HIRING)

Senior Privacy Engineer

San Mateo, CA · On-site

$119K - $163K/yr

Develop standards and guidelines that enable product teams to adopt privacy-enhancing technologies (PETs) such as differential privacy, k-anonymity, data minimization, and secure computation, with ...

You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on ...

Senior Privacy Engineer

San Mateo, CA · On-site

$119K - $163K/yr

Develop standards and guidelines that enable product teams to adopt privacy-enhancing technologies (PETs) such as differential privacy, k-anonymity, data minimization, and secure computation, with ...

AIML Privacy - Engineering Rotation

Cupertino, CA

$129K - $225K/yr

  • Medical

  • Dental

  • Retirement

Experience with differential privacy or private federated learning. BS in Computer Science, EE or equivalent experience. Pay & Benefits At Apple, base pay is one part of our total compensation ...

You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on ...

AIML Privacy - Engineering Rotation

Cupertino, CA

$129K - $225K/yr

  • Medical

  • Dental

  • Retirement

Experience with differential privacy or private federated learning. BS in Computer Science, EE or equivalent experience. Pay & Benefits At Apple, base pay is one part of our total compensation ...

Design and prototype privacy‑preserving machine‑learning algorithms (e.g., differential privacy, secure aggregation, federated learning) that can be deployed at OpenAI scale. * Measure and ...

New

Key responsibilities include working with the OpenDP team, our collaborators and community members on applying differential privacy in building software tools for data science problems, writing grant ...

Showing results 21-40

Differential Privacy information

See salary details

$99.5K

$115.5K

$129.5K

How much do differential privacy jobs pay per year?

As of Aug 19, 2026, the average yearly pay for differential privacy in the United States is $115,505.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,000.00 and $129,000.00 per year, depending on experience, location, and employer.

What is differential privacy?

Differential privacy is a mathematical framework used to ensure that individual data remains private when analyzing and sharing aggregate information from a dataset. It introduces controlled random noise to the results of queries or computations, making it difficult to determine whether any specific individual's data is included. This helps organizations gain insights from data while providing strong privacy guarantees for individuals, even against attackers with access to other information. Differential privacy is widely used in fields such as statistics, machine learning, and data publishing.

What are some common challenges faced by professionals working in differential privacy roles?

Professionals in differential privacy often encounter challenges balancing data utility with privacy guarantees, as stricter privacy controls can limit the usefulness of data for analysis. They also need to stay updated on evolving privacy regulations and technological advancements. Collaboration with data scientists, engineers, and legal teams is essential to ensure solutions meet both technical and compliance requirements. Additionally, translating complex mathematical concepts into practical, scalable systems that integrate smoothly with existing infrastructure can be a significant hurdle.

What are the key skills and qualifications needed to thrive as a differential privacy engineer, and why are they important?

To thrive as a Differential Privacy Engineer, you need a strong background in mathematics, statistics, computer science, and experience with privacy-preserving algorithms, usually supported by an advanced degree. Familiarity with programming languages like Python or R, privacy frameworks (such as Google's DP library), and knowledge of data security regulations are typically required. Excellent problem-solving skills, attention to detail, and the ability to communicate complex concepts to non-experts are crucial soft skills. These competencies are vital to designing robust privacy solutions that protect user data while enabling meaningful data analysis.

What is the difference between Differential Privacy vs Data Scientist?

AspectDifferential PrivacyData Scientist
Primary FocusProtecting individual data privacy in datasetsAnalyzing and interpreting complex data to inform business decisions
Required SkillsMathematics, privacy algorithms, data securityStatistics, programming, data visualization
Work EnvironmentResearch labs, tech companies, privacy-focused organizationsBusiness, tech firms, consulting
CertificationsPrivacy certifications, data security credentialsData science certifications, programming skills

While Differential Privacy focuses on implementing privacy-preserving techniques in data handling, Data Scientists analyze data to extract insights. Both roles require strong technical skills, but their core objectives differ: one emphasizes privacy protection, the other data analysis.

What cities are hiring for Differential Privacy jobs?

Cities with the most Differential Privacy job openings:

What states have the most Differential Privacy jobs?

States with the most job openings for Differential Privacy jobs include:

Infographic showing various Differential Privacy job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $115,505 per year, or $55.5 per hour.

Technical Strategist - Data Privacy (Python fluency)

Keystone

San Francisco, CA • On-site

$143K - $185K/yr

Full-time

Re-posted 10 days ago


Job description

Job Summary:
Keystone is a premier economics, technology, and strategy consulting firm built to help companies lead through transformation. As a Technical Strategist, you will tackle high-stakes litigation and regulatory matters involving AI, data systems, and data privacy, applying your technical expertise to navigate complex challenges.
Responsibilities:
• Work with an interdisciplinary team on litigation cases spanning AI, data analytics, digital risk, emerging technology governance, and regulatory compliance
• Build analytical models, investigative workflows, and technology assessments
• Evaluate anonymization, de-identification, and privacy-enhancing technologies (e.g., differential privacy) in the context of litigation and regulatory review
• Assess privacy and security controls, including anonymization techniques and privacy-enhancing technologies (e.g., differential privacy), in the context of regulatory and litigation scrutiny
• Contribute to the development of internal tools, libraries, and frameworks that enhance analytical consistency and scalability
Qualifications:
Required:
• Bachelor's and/or degree in Computer Science, Computer Engineering, or a related field, ideally with a focus in security or privacy
• 2+ years of professional experience developing secure software or security and privacy-related product features
• Driving technical quality and operational excellence by defining and reinforcing standards in testing, observability and system reliability
• Fluency in one or more other programming language in addition to Python
• Undergraduate level capability with data structures and algorithms
• A balance of technical excellence, intellectual curiosity, and entrepreneurial spirit suited to a fast-moving, global consulting environment
• Analytical skills with an ability to structure complex, ambiguous real-world problems
• Ability to manage multiple analytical workstreams and communicate complex findings clearly to technical and non-technical audiences
• Team player who can collaborate with multiple stakeholders and functional areas
Company:
Keystone is an innovative strategy, economics, and technology consulting firm delivering transformative ideas and novel solutions to global brands and law firms on leading-edge challenges in technology, business, consumer goods, and science. Founded in 2003, the company is headquartered in San Francisco, USA, with a team of 201-500 employees. The company is currently Growth Stage.