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Surge AI

Delivers high-quality AI training data

Corporate Counsel

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

About the Job

Requirements

  • At least 4 years of experience as a lawyer focused on commercial contracts, at a law firm or in-house.
  • Strong drafting skills and the ability to assess legal risk and prioritize important contract terms.
  • Experience with technology, software-as-a-service, data, or services agreements.
  • A practical, business-minded approach that provides clear answers and helps teams reach agreements.
  • Ability to own a high volume of work and prioritize independently.
  • Interest in building forms and processes, not only using existing ones.
  • Genuine curiosity about artificial intelligence and the companies building it.

Responsibilities

  • Manage standard customer and vendor agreements and keep forms current.
  • Review incoming contracts in the first round and advise the business on material terms and priorities.
  • Partner with Business Development and Growth to implement new product and business ideas.
  • Design and maintain forms, templates, and playbooks so routine agreements can be handled without a lawyer each time.
  • Take on negotiations, initially with support as needed and with increasing independence over time.
  • Work with IP and Data Privacy Counsel and Labor Counsel on contract terms in their areas.
  • Handle other corporate and commercial questions as they arise.

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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