
Artificial Intelligence • B2B • SaaS
Summa Linguae Technologies is a company that provides tech-enabled language solutions for global, content-rich companies facing multilingual data challenges. They offer data solutions for artificial intelligence, including data collection, annotation, and testing solutions to power AI and translation models. In addition, they provide technology-enabled localization and translation solutions that combine automation and human expertise. Summa Linguae Technologies also offers managed services, including staffing and project management solutions to optimize localization efforts. Their mission is to facilitate seamless communication between their clients and their global customer base through multilingual data management solutions, leveraging data, automation, and human expertise.
201 - 500 employees
🤖 Artificial Intelligence
🤝 B2B
☁️ SaaS
October 29
🗽 New York – Remote
💵 $100 / hour
⏳ Contract/Temporary
🟠 Senior
🔴 Lead
💸 Financial Planning and Analysis (FP&A)

Artificial Intelligence • B2B • SaaS
Summa Linguae Technologies is a company that provides tech-enabled language solutions for global, content-rich companies facing multilingual data challenges. They offer data solutions for artificial intelligence, including data collection, annotation, and testing solutions to power AI and translation models. In addition, they provide technology-enabled localization and translation solutions that combine automation and human expertise. Summa Linguae Technologies also offers managed services, including staffing and project management solutions to optimize localization efforts. Their mission is to facilitate seamless communication between their clients and their global customer base through multilingual data management solutions, leveraging data, automation, and human expertise.
201 - 500 employees
🤖 Artificial Intelligence
🤝 B2B
☁️ SaaS
• Collaborate with AI and engineering teams to define research-based workflows. • Develop evaluations and test cases for assessing workflows. • Design evaluations to assess LLM capabilities in financial tasks. • Guide on curating financial data for training LLM. • Provide feedback on LLM performance and suggest improvements.
• 12+ years of practical, professional experience in Investment Banking, Private Equity, Asset Management, or Equity Research. • Strong analytical and critical thinking abilities. • Excellent communication skills. • A basic understanding of AI and machine learning is a significant plus. • Meticulous attention to detail.
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