Company Description:
TaskMaster Virtual Ally helps AI enterprise organizations eliminate the Data Fidelity problem and close the Data Readiness Gap that slows down AI adoption by transforming messy, unstructured information into pristine, reliable, machine-readable, and usable data.
The company delivers Human Infrastructure as a Service (HIaaS), embedding secure human-in-the-loop Pods directly into client environments to normalize inputs, resolve edge cases, and continuously improve AI models through RLHF.
TaskMaster works primarily with AI Frontier Enterprise in the Health Tech, FinTech, and Enterprise SaaS domain, operating under strict Zero-Retention policies and VDI/VPN security standards so that no data leaves the client’s network.
As a Florida-registered LLC, TaskMaster keeps all contracts, data privacy, and compliance under U.S. legal jurisdiction, offering a secure and compliant environment for both clients and team members.
Role Description:
The Mathematics Domain Subject Matter Expert (L2 SME) is a remote, contract role focused on ensuring the accuracy and quality of mathematics-related content and data. This role involves reviewing, solving, and validating mathematical problems, identifying edge cases, and providing clear, structured explanations suitable for educational and AI training contexts.
The L2 SME collaborates with internal teams to refine math curricula, suggest improvements to problem sets, and support the development of high-quality instructional materials. Daily tasks include analyzing complex math queries, providing expert guidance on mathematical reasoning, and documenting feedback in a clear, consistent format to support continuous model improvement. The SME is expected to work independently, meet turnaround times, and maintain strict adherence to TaskMaster’s security and compliance standards.
Engagement:
Project-Based / Pod Deployment (20-Activity Calibration Pilot Phased to Enterprise Scale-Up)
Qualifications (Core Required Skills):
- Strong formal background in Mathematics (Linear Algebra, Probability & Statistics, Calculus, Discrete Math)
- Ability to evaluate, construct, and validate complex quantitative problems and proofs with extreme rigor • Comfortable working within structured task guidelines and acceptance criteria
- Basic Python literacy (ability to review or lightly modify computational scripts)
- Preferred: Background in RLHF, AI data annotation, technical writing, or quantitative tutoring/teaching. Prior experience as a teacher, tutor, academic reviewer, or subject matter expert in math-focused roles is highly beneficial.
- Ability to work remotely under strict data security guidelines, follow structured workflows, and meet deadlines reliably.
- Familiarity with digital learning platforms, LaTeX or equation editors, and collaborative documentation tools is a plus.
What We Offer:
• 100% remote work supporting tier-1 enterprise AI models from the Philippines.
• Structured, high-status Pod culture rather than high-volume crowd platforms.
• Direct pathway from the Calibration Pilot to long-term enterprise deployment.
• Above industry-standard pay grade so you don't need to leave your family.
How to Apply:
Submit your letter of application and a link to your 1-minute video introduction introducing yourself and why you think you are the best person for this role.
Send it to [email protected] with the subject line Math SME.