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Surge AI

Delivers high-quality AI training data

Labor Counsel

Legal Counsel & Legal SupportConfirmed live in the last 24 hours
Full-timeRemote in USANo salary listedRemote

About the Job

Requirements

  • Five to ten years of experience in labor and employment law, in a law firm or in-house.
  • Broad experience across regulatory and compliance work and litigation.
  • Experience with worker classification.
  • Experience on the plaintiff side is welcome but not required; it is not a requirement.

Responsibilities

  • Advise on worker classification for employees and contractors, and help design and review how the company engages with its people.
  • Advise on wage and hour, leave, termination, and other employment compliance questions across the jurisdictions in which the company operates.
  • Work with HR and the teams managing the expert workforce to build and update policies, procedures, and compliance practices.
  • Manage claims, demand letters, agency charges, and disputes, and work with outside counsel on litigation.
  • Review and update employee communications and onboarding and offboarding forms.
  • Work with HR on HR systems and data so legal requirements are built into the tools teams use.
  • Investigate and advise on employee relations issues alongside HR.
  • Help HR and managers understand the legal reasons behind rules in plain language.

Desired Qualifications

  • Experience with HRIS systems is preferred.
  • Experience on the plaintiff side is welcome but not required.

About the Company

Surge AI

Delivers high-quality AI training data

Surge AI provides high-quality training and evaluation data for AI models. It creates human-annotated datasets, preference data, and reinforcement learning from human feedback (RLHF) to help developers of large language models and other machine learning systems improve accuracy, alignment, and real-world performance, especially for advanced generative AI tasks. The company targets the high end of the data labeling market by prioritizing quality, scalability, and the ability to handle complex, model-critical labeling rather than simple commodity annotations. Its goal is to support better-performing, safer, and more reliable AI systems by delivering data that directly feeds model training and evaluation.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
San Francisco, CA
Founded
2020

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