Staff AI Engineer, AI Privacy Specialist

Team & Role Overview :

The Responsible AI team at LinkedIn serves as the centralized hub of excellence for AI and Data Science spearheading the technical and organizational strategy to ensure trust compliance and safety for all LinkedIn members and clients. We ensure LinkedIns AI solutions are aligned with principles of Fairness Inclusion Transparency and now advanced post-training LLM alignment work. Our work involves fine-tuning and aligning large language models with LinkedIns core principles focusing on critical areas such as privacy fairness explainability safety hallucination reduction and robustness.

This team drives applied research and the development of scalable industry-leading solutions across LinkedIns AI platforms models and products.

Location :

At LinkedIn our approach to flexible work is centered on trust and optimized for culture connection clarity and the evolving needs of our business. The work location of this role is hybrid meaning it will be performed both from home and from a LinkedIn office on select days as determined by the business needs of the team.

This role will be based in Sunnyvale CA

Responsibilities :

Conduct independent hands-on research into the state-of-the-art in differential privacy secure computation and privacy-preserving machine learning.

Evaluate adapt and implement advanced algorithmic approaches to optimize for data utility and privacy guarantees in production environments.

Establish and manage rigorous evaluation frameworks to quantify the fidelity utility and privacy guarantees of generated and anonymized data.

Partner with cross-functional teams of data scientists software engineers product managers and governance specialists to ensure the seamless integration and adoption of new privacy capabilities across the enterprise.

Develop privacy-first training algorithms and techniques

Develop evaluation and auditing techniques to measure the privacy of training algorithms

Design and prototype privacy-preserving machine-learning algorithms (e.g. differential privacy secure aggregation federated learning) that can be deployed at enterprise scale.

Measure and strengthen model robustness against privacy attacks such as membership inference model inversion and data memorization leaksbalancing utility with provable guarantees.

Develop internal libraries evaluation suites and documentation that make cutting-edge privacy techniques accessible to engineering and research teams.

Lead deep-dive investigations into the privacyperformance trade-offs of large models publishing insights that inform model-training and product-safety decisions.

Define and codify privacy standards threat models and audit procedures that guide the entire ML lifecyclefrom dataset curation to post-deployment monitoring.

Collaborate across Security Policy Product and Legal to translate evolving regulatory requirements into practical technical safeguards and tooling.

Provide technical leadership and mentorship to a team of engineers fostering a culture of innovation and excellence.

Qualifications :

Basic Qualifications :

At least one year of experience as a Technical Lead or equivalent.

4 years of overall experience in AI or ML Engineering.

BA / BS Degree in Computer Science or related technical discipline or equivalent practical experience

Preferred Qualifications :

6 years of overall industry and / or full time research experience.

PhD in Privacy Security & Trust or a related discipline.

Extensive experience with Differential Privacy Federated Learning AI Modeling and other related solutions.

Demonstrated experience effectively collaborating with various teams across the organization including Engineering Product Legal / Compliance etc.

Suggested Skills : Differential Privacy

AI Privacy

AI Modeling

Additional Information :

You will Benefit from our Culture :

We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.

Compensation :

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $170000 - $277000. Actual compensation packages are based on a wide array of factors unique to each candidate including but not limited to skill set years & depth of experience certifications and specific office location. This may differ in other locations due to cost of labor considerations.

The total compensation package for this position may also include annual performance bonus stock benefits and / or other applicable incentive compensation plans. For additional information visit : Opportunity Statement

We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race color religion creed gender national origin age disability veteran status marital status pregnancy sex gender expression or identity sexual orientation citizenship or any other legally protected class.

LinkedIn is committed to offering an inclusive and accessible experience for all job seekers including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.

If you need a reasonable accommodation to search for a job opening apply for a position or participate in the interview process connect with us at and describe the specific accommodation requested for a disability-related limitation.

Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to :

• Documents in alternate formats or read aloud to you
• Having interviews in an accessible location
• Being accompanied by a service dog
• Having a sign language interpreter present for the interview

A request for an accommodation will be responded to within three business days. However non-disability related requests such as following up on an application will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about discussed or disclosed their own pay or the pay of another employee or applicant. However employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information unless the disclosure is (a) in response to a formal complaint or charge (b) in furtherance of an investigation proceeding hearing or action including an investigation conducted by LinkedIn or (c) consistent with LinkedIns legal duty to furnish information.

San Francisco Fair Chance Ordinance

Pursuant to the San Francisco Fair Chance Ordinance LinkedIn will consider for employment qualified applicants with arrest and conviction records.

Pay Transparency Policy Statement

As a federal contractor LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link : Data Privacy Notice for Job Candidates

Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants : Work :

No

Employment Type : Full-time

Key Skills

Computer Science,Docker,Kubernetes,Python,VMware,C / C++,Go,System Architecture,gRPC,OS Kernels,Perl,Distributed Systems

Department / Functional Area : Engineering

Experience : years

Vacancy : 1