Job Description

This role will be based in Mountain View CA.

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.

HALO (Human Judgment Annotation Localization and Operations) is a horizontal team within Core AI that partners across the company to enable high-quality human judgment for AI development. We partner closely with cross-functional stakeholders and internal teams to define quality goals design evaluation and data pipelines and scale repeatable measurement systems. Our work spans multiple initiatives at once supported by shared standards platforms and best practices that help teams move faster without compromising quality.

Key Responsibilities

• Be part of working groups with Engineering Product Vendor Operations etc. to align on quality goals tradeoffs and deliverables for assigned projects
• Create annotation tasks end-to-end (rubrics rating scales decision rules examples) and translate ambiguous behaviors into measurable criteria
• Perform hands-on annotation and task completion for complex or high-impact cases to establish ground truth and calibrate guidelines
• Build and operate scalable annotation and evaluation workflows on vendor or in-house platforms (task design routing sampling quality assurance gates)
• Support vendor and internal workforce execution through clear instructions training materials calibration support and ongoing quality loops
• Implement quality controls such as audits inter-annotator agreement tracking adjudication processes and drift checks
• Use AI tools to improve workflow speed and consistency (LLM-assisted prompting hybrid labeling and evaluation automated checks) with reliability controls
• Create and validate datasets and evaluations used for training and assessing models and agents; perform error analysis and drive iteration with partners
• Run practical experiments to improve quality or efficiency (rubric prompt task design sampling changes) and document outcomes
• Contribute requirements and feedback for workflow and tooling improvements

Qualifications :

Required Qualifications

• Bachelor of Arts or Bachelor of Science in Computational Linguistics Linguistics Language Technologies or related field
• 1 year industry experience in human judgment annotation or evaluation supporting AI development
• Experience creating rubrics or guidelines and producing labeled datasets or evaluation results used for AI training or evaluation
• Experience operating scaled workflows using vendors or contractor workforces and annotation or evaluation platforms
• Experience applying generative AI tools in data or evaluation workflows (prompt iteration hybrid review automated checks)
• Python (or equivalent) for dataset quality assurance metrics sampling and analysis (analysis scripting; not production software engineering)
• Demonstrated ownership of small-to-medium projects from scope through delivery

• Strong written and verbal communication; able to document decisions standards and results clearly

Preferred Qualifications

• Master of Science (or higher) in a relevant field
• Experience building repeatable evaluation components (scorecards regression sets lightweight monitoring)
• Familiarity with Jupyter and Git (or equivalent)
• Experience evaluating multi-step or agentic behavior using scenario-based evaluations and failure mode tracking
• Experience supporting multi-market evaluation consistency with localization or language experts

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. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $88000 - $144000. 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 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

Job Tags

Similar Jobs