Job Category: Subject Matter Expertise

Mercor is partnering with a leading AI research lab to build next-generation text-to-speech (TTS) systems capable of producing natural, expressive, and human-like voices. We are seeking USA-based African American voice actors to contribute high-quality voice recordings for training and evaluating cutting-edge speech models. This role is open to both experienced voice professionals and newcomers with a naturally clear, expressive voice and a good recording setup — prior voice-acting experience is a plus but not required.

Mercor is looking for detail-oriented individuals with 2-3 years of experience in STEM, non-STEM fields, or currently enrolled postgrad college students to support a research project with a leading AI lab. You will help benchmark and improve cutting-edge AI models. Required: All experts on this project must have a Macbook device with an ‘M’ series chip to perform tasks on.

We’re hiring an Expert Project Manager to help run projects that push the frontier of LLM browsing capabilities. Day to day: tracking project and annotator performance in Google Sheets, reviewing annotator quality, handling contributor communications, and more. We’re looking for someone with high agency, strong organization, an analytical mindset, and real investment in seeing LLM training projects succeed.

Mercor is building a network of experienced data scientists for potential future projects with leading AI research organizations. These projects may focus on evaluating how effectively AI systems perform real-world data science work. There is no immediate project opening, but qualified applicants may be contacted as relevant opportunities become available.

Mercor is partnering with a leading AI research lab to build next-generation text-to-speech (TTS) systems capable of producing natural, expressive, and human-like voices. We are seeking Northern UK-based female voice actors with authentic Northern English accents (e.g. Yorkshire, Manchester, Newcastle, Liverpool) to contribute high-quality voice recordings for training and evaluating cutting-edge speech models.

Mercor is building a network of experienced management consultants for potential future projects with leading AI research organizations. These projects may focus on evaluating how effectively AI systems perform real-world consulting work. There is no immediate project opening, but qualified applicants may be contacted as relevant opportunities become available.

Mercor is recruiting participants for the Youth Well-being Project , a research study led by Stanford University in collaboration with Bocconi University , focused on how smartphones and digital tools affect children and families. 📋 Applications are open now. We’re accepting applications at this stage to finalize and confirm participants for the upcoming batch, which begins in January.

Mercor is partnering with a leading AI research lab to build next-generation text-to-speech (TTS) systems capable of producing natural, expressive, and human-like voices. We are seeking Australia-based native English speakers with authentic Australian accents to contribute high-quality voice recordings for training and evaluating cutting-edge speech models. This role is open to both experienced voice professionals and newcomers with a naturally clear, expressive voice and a good recording setup — prior voice-acting experience is a plus but not required.

Mercor is seeking experimental scientists and engineers across inorganic synthesis, characterization, superconductors, and semiconductors (including advanced packaging) to support a frontier AI research lab building models for materials science and the physical sciences. This is hands-on, expert-level work: you’ll apply deep, specialized knowledge to generate, structure, and evaluate the scientific data these models learn from — and your input will directly shape how advanced models reason about materials, devices, and processes. Contribute domain expertise across synthesis, characterization,

We’re looking for engineers who have shipped production search systems (especially agentic ones now that we’re in the era of LLMs and agents) and are thinking hard about the requirements and optimizations of those systems. Owned relevance or retrieval on a system real users depended on. Decided how to quantify impact and improvements with these systems.