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Work Location : Remote, within US
Engagement Model : Independent Contractor/Freelance
Estimated Start Date : ASAP
We are looking for highly qualified STEM graduate‑level candidates to contribute to generative AI initiatives. This role involves supporting data collection and evaluation workflows, collaborating closely with AI researchers, and ensuring the development of high‑quality STEM focused content. It is a hands‑on position that blends subject matter knowledge with strong analytical and instructional capabilities.
Main Responsibilities:
Work with AI researchers and engineers to understand data collection and evaluation needs.
Translate requirements into clear workflows for larger teams.
Execute and manage data workflows quickly and with high quality.
Create new and efficient methods for collecting and evaluating STEM-related data.
Collaborate with peers and cross-functional teams to deliver large volumes of accurate data.
Requirements:
Currently enrolled Master’s students or early‑stage PhD candidates in Computer Science, Mathematics, Physics, Electrical Engineering, or related STEM fields.
Technical & Quantitative Competitions: Participation or strong performance in recognized mathematics, computing, or physics competitions at the national or international level.
Advanced Tech Challenges: High achievement in prestigious problem‑solving or programming competitions at the collegiate or global stage.
Academic Excellence: Graduated at the top of the undergraduate class or achieved outstanding academic standing from a highly competitive engineering, mathematics, or pre‑medical program.
Intermediate knowledge of Python and familiarity with Google Colab are required.
DataForce by TransPerfect is part of the TransPerfect family of companies, the world’s largest provider of language and technology solutions for global business, with offices in more than 100 cities worldwide.
We offer high-quality data for Human-Machine Interaction to some of the most prestigious technology companies in the world. Our department focuses on gathering, enriching and processing data for Machine Learning in different AI domains.
