Company Description
LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.
Join us to transform the way the world works.
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
- Lead cross-functional alignment with Engineering, Product, Data Science, domain SMEs, Trust/Legal, TPM, and vendor operations on evaluation strategy, quality goals, tradeoffs, and delivery across multiple initiatives
- Define and evolve evaluation frameworks for complex model and agent behaviors, including rubrics, rating scales, defect taxonomies, escalation criteria, and market-specific guidance for ambiguous, multi-step, and high-impact use cases
- Own end-to-end evaluation systems, including metrics, scorecards, regression sets, monitoring plans, scenario suites, and success criteria, and ensure outputs are repeatable, decision-useful, and adopted by partner teams
- Design and operationalize annotation and evaluation pipelines across internal and vendor platforms, including task design, QA gates, adjudication approaches, workflow maintenance, and documentation
- Drive development of human, synthetic, and adversarial datasets to improve evaluation coverage, identify blind spots, and support model iteration, LLM-as-a-judge systems, and reward model development
- Lead calibration strategy and disagreement analysis across human and model judgments; identify drift, root causes, and reliability issues, and translate findings into guideline updates, new edge cases, retraining opportunities, and product quality improvements
- Set and uphold quality standards for vendor and internal workforces, including onboarding, guideline training, audit design, escalation handling, and cost-quality tradeoff decisions across medium-to-large programs
- Lead error analysis and evaluation experiments; synthesize findings into clear recommendations and influence roadmap, launch readiness, and quality investments
- Define requirements for human judgment and evaluation tooling, and partner with Engineering on design, testing, rollout, and adoption
- Create reusable standards and best practices that scale across teams, and enable partners on methodology, score interpretation, and appropriate use of evaluation outputs
- Mentor junior team members on evaluation design, annotation quality, analysis methods, and operational excellence
- Demonstrate learning agility in a rapidly evolving field by incorporating new tools, methods, and research into evaluation strategy and workflows
- Apply native-speaker linguistic and cultural expertise in French (France), German (Germany), Spanish (Spain), Portuguese (Brazil), or other i18n market(s) to define market-appropriate quality standards and improve consistency across locales
Qualifications
Basic Qualifications
- BA/BS in Computational Linguistics, Linguistics, Language Technologies, or a related field
- 4+ years of industry experience owning end-to-end human judgment, operations, and quality workflows for AI development
- Proven experience leading medium-to-large evaluation or annotation programs in production environments
- Experience working cross-functionally with partners such as Engineering, Product, and Data Science to drive decisions and execution
- Experience developing evaluation frameworks for complex model or agent behaviors
- Experience building or improving scalable evaluation or annotation workflows
- Experience working with datasets and evaluation methods for LLMs or agentic systems
- Experience analyzing quality signals and using findings to improve guidelines, workflows, or model performance
- Experience with Python, or an equivalent language, for analysis, experimentation, metrics, or quality validation
- Ability to communicate clearly in writing and verbally, including documenting decisions and aligning across functions
Preferred Qualifications
- 5-7 years of overall industry experience
- MS or PhD in Computational Linguistics, Linguistics, Language Technologies or a related field
- Experience in more ambiguous, high-impact, or fast-evolving AI product areas
- Experience with LLM-as-a-judge, reward modeling, or model-based evaluation approaches
- Experience creating standards or frameworks used across multiple teams
- Experience influencing product or quality direction through evaluation insights
- Experience mentoring others in evaluation, annotation, or quality methods
- Experience supporting i18n evaluation or linguistic quality across markets
Suggested Skills
- Strategic Evaluation Design for Complex AI Systems
- Quality Governance and Standards at Organizational Scale
- Human Judgment, Vendor, and Workforce Strategy
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 $133,000 - 216,000. 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 https://careers.linkedin.com/benefits.
Additional 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 accommodations@linkedin.com 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 LinkedIn's 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: https://lnkd.in/paytransparency.
Global 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: https://legal.linkedin.com/candidate-portal.
