Senior Staff Software Engineer, AI Infrastructure

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. 

Join us in building the AI Governance Platform that ensures LinkedIns Models are ready and safe to operate in production.

LinkedIns AI Governance Platform sits in the critical path between model development and production deployment. It serves as a centralized control layer in the deployment path for machine learning models across recommendations search ads GenAI and other AI-powered experiences helping determine whether models are ready to move into production.

The team builds large-scale metadata-driven distributed systems that capture signals throughout the ML lifecycle process high volumes of model and system metadata execute model validation and evaluation workflows and apply automated policy-based guardrails before models reach production. These systems enable LinkedIn to consistently enforce standards around fairness bias privacy security safety and overall model quality.

The platform must operate at the speed and scale of LinkedIns ML ecosystem supporting continuous model training evaluation and high-velocity deployment while translating evolving AI governance requirements into scalable repeatable and enforceable engineering capabilities.

As a Sr. Staff Software Engineer you will help define the architecture and technical strategy for LinkedIns next generation of AI Governance infrastructure. You will solve complex distributed systems metadata management and ML infrastructure problems while influencing how trusted and compliant AI practices are implemented across the company.

You will partner closely with ML engineers researchers infrastructure teams product organizations privacy security and Responsible AI teams to build foundational systems that enable AI to be developed evaluated and deployed safely and consistently at LinkedIn.

Responsibilities

• Own the technical strategy and architecture for LinkedIns large-scale AI Governance model validation and policy enforcement infrastructure.

• Design and build high-scale metadata-driven distributed systems that ingest process store and analyze model lifecycle metadata evaluation results production signals and model outputs.

• Build scalable validation and automated gating systems that support continuous model training and high-velocity deployment while determining whether models meet production standards.

• Translate governance requirements around fairness bias privacy security safety and model quality into automated enforceable platform policies.

• Develop evaluation and analysis frameworks that assess model behavior and generate signals used in governance workflows and production release decisions.

• Build platforms APIs SDKs and abstractions that integrate governance validation lineage and lifecycle tracking into ML development and deployment workflows.

• Partner with ML AI research infrastructure Responsible AI privacy security and product teams to define technical standards and scalable governance solutions.

• Provide Sr. Staff-level technical leadership by influencing architecture across teams improving developer productivity mentoring engineers and raising the technical bar for AI infrastructure.

Qualifications :

Basic Qualifications

• BS/BA in Computer Science or related technical field or equivalent technical experience.

• 5 years of industry experience in software design development and algorithm-related solutions.

• 5 years of experience programming in languages such as Python C Java Go Rust or Scala.

• 2 years of experience as an architect technical lead or in another technical leadership position.

• 5 years of experience building large-scale infrastructure data platforms machine learning systems or distributed systems.

• Hands-on experience designing and developing distributed systems or other large-scale production platforms.

• Experience designing or working with metadata systems data platforms large-scale storage systems or data-processing pipelines used to capture and reason over complex system or ML lifecycle state.

• Experience working with machine learning systems or production ML lifecycle workflows such as training evaluation validation inference or deployment.

Preferred Qualifications

• MS or PhD in Computer Science or related technical discipline.

• 10 years of experience in software design and development including significant experience in technical leadership positions.

• 5 years of experience designing and building large-scale distributed systems and production infrastructure.

• Experience building machine learning infrastructure MLOps platforms model lifecycle systems or production ML platforms.

• Experience building AI governance model validation model compliance Responsible AI trust and safety or policy enforcement systems.

• Experience designing metadata platforms data models data pipelines feature stores model registries lineage systems or other platforms that track ML lifecycle information.

• Experience building systems that evaluate model behavior or enforce requirements related to fairness bias privacy safety security or model quality.

• Experience building automated validation policy decisioning deployment gating or compliance enforcement systems.

• Experience building developer-facing APIs SDKs frameworks or platform abstractions used across multiple engineering teams.

• Demonstrated ability to define technical strategy and influence architecture across organizational and team boundaries.

Suggested Skills

• AI Governance / Responsible AI

• Machine Learning Infrastructure / MLOps

• Model Lifecycle & Model Validation

• Metadata Platforms

• Policy Enforcement / Automated Guardrails

• Model Evaluation

• Fairness / Bias / Privacy

• Large-Scale Distributed Systems

• Data Platforms / Data Pipelines

• Production Machine Learning Systems

• Technical Leadership

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $198000 to $326000. Actual compensation packages are based on several factors that are unique to each candidate including but not limited to skill set depth of experience certifications and specific work location. This may be different in other locations due to differences in the cost of labor.

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

Equal 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 and describe the specific Accommodation requested for a disability-related limitation.
Fill out an Accommodation request here: 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 and Compliance Posters for Job Candidates 

Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: Work :

No

Employment Type :

Full-time