Senior AI Linguist

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.

Role Summary

AI is evolving rapidly and high-performing teams win by defining quality clearly building reliable ground truth and scaling human judgment without slowing innovation. HALO makes that possible.

The AI Linguist plays a key role in shaping the quality of LinkedIns AI systems across a wide range of use cases experiences and product areas including but not limited to relevance ranking rationale quality and emerging multi-step and agentic capabilities. This role turns ambiguity into clear evaluation standards by designing annotation tasks and rubrics producing high-quality ground truth through hands-on annotation and building frameworks that make AI systems models and agents trainable measurable and continuously improvable.

The role also drives scalable annotation and evaluation pipelines conducts audits of internal and vendor-produced work and helps ensure strong inter-annotator agreement and consistently high quality. Working at the intersection of human expertise and modern AI tooling the AI Linguist applies methods such as LLM-assisted prompting hybrid labeling and evaluation automated checks regression testing continuous monitoring to support evolving business and product needs.

The datasets rubrics and evaluation signals produced in this role become shared standards across LinkedIn directly influencing how AI systems are trained evaluated and improved. This is a great opportunity for someone who thrives in ambiguity builds frameworks that others depend on and wants to shape how AI performs in the real world.

Key Responsibilities

• Partner cross-functionally with Engineering Product Data Science domain SMEs Trust/Legal TPM and vendor ops to align on quality goals tradeoffs and delivery plans

• Define measurable quality criteria for ambiguous behaviors (rubrics rating scales concepts failure modes) and ensure consistency across markets

• Design and run repeatable evaluation systems (metrics scorecards regression sets monitoring plans) including multi-step/agentic behavior evaluation using scenario suites and success criteria

• Build scalable high-quality annotation/evaluation pipelines including hands-on execution of annotation task covering task design sampling QA gates adjudication maintenance) on vendor and/or in-house platforms

• Lead vendor and internal workforce execution at scale owning training and onboarding calibration sessions periodic reviews/audits of internal Linguists and vendors annotation output to measure and improve inter-annotator agreement quality escalations and adjudication and ongoing cost/quality tradeoffs to consistently maintain high annotation quality

• Establish and enforce quality governance (agreement targets drift/bias checks defect taxonomy)

• Leverage AI tools to scale work (LLM-assisted prompting hybrid labeling/evaluation automated checks) while maintaining reliability controls

• Run method/workflow experiments; document results and drive decisions based on evidence

• Perform error analysis and drive iteration cycles with partners; translate findings into actionable changes

• Define platform/tool requirements for human judgment workflows; partner through build/test/deploy and adoption

• Publish reusable best practices and standards; mentor junior Linguists and conduct design/analysis reviews across initiatives

Qualifications :

Basic Qualifications

• BA/BS in Computational Linguistics Linguistics Language Technologies or related field

• 2 years industry experience in human judgment/annotation/evaluation supporting AI development

• Proven ownership of medium-to-large evaluation or annotation initiatives (method delivery)

• Demonstrated cross-functional collaboration (Engineering/Product/Data partners) and ability to manage tradeoffs and dependencies

• Experience designing large-scale pipelines with QA governance and maintenance plans including vendor/platform-based workflows

• Experience converting ambiguity into measurable criteria and repeatable evaluation methods

• Experience in applying AI-assisted data workflows as well as creating datasets for LLMs and agentic systems prompt-based labeling and evaluation hybrid human-in-the-loop review automated validation/consistency checks and iterative dataset building to improve model and agent performance

• Proficiency in Python (or equivalent) for analysis/experimentation building metrics sampling and to validate annotation/evaluation quality (analysis-focused; not production software engineering)

• Ability to communicate  cross-functionally and document decisions

Preferred Qualifications

• MS/PhD in a relevant field

• Experience supporting multi-market evaluation/annotation consistency (partnering with localization/language experts)

• Experience evaluating multi-step/agentic behavior with scenario suites failure mode taxonomies and continuous evaluation loops

• Experience scaling standards and frameworks across multiple teams

• Experience building semi-automated evaluation components (scorecards monitoring regression suites)

• Ability to execute across multiple concurrent initiatives

Suggested Skills

• AI evaluation and annotation frameworks

• Agentic AI Quality governance and human-judgment operations

• Cross-functional AI program execution

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 $141000 - $252500. 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 :

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No

Employment Type :

Full-time