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Subject Matter Expert (Sports) - Remote

Posted Yesterday
All others
Freelance
USA

Overview

DataForce by TransPerfect is seeking experienced Sports Subject Matter Experts with deep expertise in various sports to support the development of next-generation AI technologies in the sports domain.

In Short

  • Work location is remote, anywhere within the US.
  • Engagement model is freelance/independent contractor.
  • Weekly workload of up to 40 hours per week.
  • Professional experience required in sports journalism, commentary, analysis, coaching, or as a former athlete.
  • Opportunity to work on innovative projects combining sports knowledge and AI.
  • Generate and validate high-quality sports data for AI training.
  • Support design of sports-aware AI architectures.
  • Evaluate AI outputs for accuracy and relevance.
  • Provide expert feedback on model performance.
  • Assist in building benchmark datasets for AI competence measurement.

Requirements

  • 5+ years of professional experience in relevant sports fields.
  • Ability to explain complex sports scenarios clearly.
  • Interest in AI/ML and sports analytics.
  • Excellent analytical and communication skills.
  • Preferred experience in AI, machine learning, or computational research projects.

Benefits

  • Work on innovative projects in the sports domain.
  • Flexible working hours.
  • Opportunity to influence AI technologies in sports.
  • Collaboration with a global leader in language and technology solutions.
  • Access to a network of prestigious technology companies.
TransPerfect logo

TransPerfect

TransPerfect is the world’s largest provider of language and technology solutions for global business, with a presence in over 100 cities worldwide. The company offers high-quality data for Human-Machine Interaction, catering to some of the most prestigious technology companies. Their DataForce division specializes in gathering, enriching, and processing data for Machine Learning across various AI domains, ensuring the development of advanced machine learning systems such as neural networks and generative models.

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