• You support international insurers in implementing transformation and digitalization programs • You analyze end-to-end insurance processes as well as existing IT and system landscapes and identify concrete improvement opportunities • You contribute to the development and modernization of core insurance processes and support their technical and functional implementation • You design solutions at the interface between business and IT, ensuring requirements are translated into actionable concepts • You actively participate in automation and AI initiatives to increase efficiency and improve decision quality in insurance processes • You take ownership of work packages or subprojects and collaborate closely with international project teams and clients

Role Description - Design ML/LLM evaluation tasks, rubrics, and metrics to enhance model performance. - Grade model/agent outputs and improve evaluation quality through thorough review. - Apply training-side judgment in SFT, RLHF, and reward modeling to evaluation design. - Collaborate with AI research teams to refine evaluation signals and improve model outputs. - Work independently and asynchronously to meet deadlines and improve AI model performance. Qualifications - Must-Have: 5+ years as a Machine Learning Engineer with hands-on training and evaluation experience. - Proficiency in PyTorch, JAX, and Hugging Face. - Strong written communication skills. - Preferred: Fluency in SFT, RLHF, reward modeling, and evaluation metrics. Requirements - Interview Process: - Mercor Technical Screen: Short assessment. - Live Code Review Session: Interactive evaluation. - Domain Expert Interview: In-depth discussion. - You're paid $200 for completing all three, regardless of outcome. Benefits - Application Process (Takes 20–30 mins to complete): - Upload resume - AI interview based on your resume - Submit form - Resources & Support: - For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome - For any help or support, reach out to: support@mercor.com - Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Role Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: IP Law Expert Type: Contract Compensation: $1,750–$2,150 per completed task Location: Remote Role Responsibilities - Build a realistic digital workspace centered on the Drive folders you use day-to-day, including client memos, patent/trademark drafts, prior-art search results, opinion letters, licensing agreements, docket printouts, and email threads. - Represent platforms like Westlaw/LexisNexis, HotDocs, and Relativity. - Design multi-step tasks grounded in real workflows, structuring around end-to-end client engagements that require navigation of multiple apps, files, and stakeholders to challenge frontier AI agents. - Collaborate with other IP attorneys to design the environment, shape task scope, and review scenarios for realism and rigor. - Work asynchronously with research teams to refine task designs and evaluation criteria for IP-law agent benchmarks. - Contribute to frontier AI research and benchmarking, with work produced directly informing how leading labs train and evaluate the next generation of AI systems. Qualifications - Must-Have JD and active bar admission; USPTO registration for patent practitioners. - 3+ years of full-time IP experience at an AmLaw 100/200 firm or Fortune 500 in-house IP team. - Background in patent prosecution, trademark portfolio management, IP litigation, or licensing. - Day-to-day use of Westlaw/LexisNexis, HotDocs, or Contract Express, and Relativity. - Strong analytical thinking and writing skills. Requirements - Task Completion Pay: Competitive and based on task quality. - Performance Bonus: Weekly bonus incentive for top performers. - Hourly Opportunity: Transition to hourly compensation based on sustained quality and throughput. Application Process - Upload resume - AI interview based on your resume - Submit form Resources & Support - For details about the interview process and platform information, please check: Interview Process - For any help or support, reach out to: support@mercor.com - Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Role Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Education Technology Expert Type: Contract Compensation: $850–$1,000 per completed task Location: Remote Role Responsibilities - Build a realistic digital workspace centered on the Drive folders you use daily, including: - Product specs - Learning-design docs - Assessment rubrics - Engagement reports - Integration plans - PD materials - Email threads - Represent platforms like Google Classroom, PowerSchool, and Google Forms. - Design multi-step tasks grounded in your real workflows, requiring navigation of multiple apps, files, and stakeholders to challenge frontier AI agents meaningfully. - Collaborate with other education-technology experts to design the environment, shape task scope, and review scenarios for realism and rigor. - Work asynchronously with research teams to refine task designs and evaluation criteria for ed-tech agent benchmarks. - Contribute to frontier AI research and benchmarking, directly informing how leading labs train and evaluate the next generation of AI systems. Qualifications - 3+ years of full-time experience at a Fortune 500 ed-tech company, R1 university, or major K-12 district/state-level education agency. - Background in: - LMS administration - Educational product management - Learning engineering - Instructional design - Learning analytics - Assessment design - Adaptive-learning platforms - District-level ed-tech leadership - Compliance with student-data regulations (FERPA, COPPA) and accessibility (WCAG, Section 508). - Day-to-day use of Google Classroom, PowerSchool, Infinite Campus, and Google Forms. - Strong analytical thinking and writing, able to translate ed-tech workflows into structured task specs. Requirements - Task Completion Pay: Competitive and based on task quality (~$850–$1,000 per completed task, subject to change as the project evolves). - Performance Bonus: Top performers receive a weekly bonus incentive on top of their per task rate. - Hourly Opportunity: Top performers may be invited to transition to an hourly compensation model based on sustained quality and throughput. Application Process - Upload resume - AI interview based on your resume - Submit form Resources & Support - For details about the interview process and platform information, please check: Interview Process - For any help or support, reach out to: support@mercor.com PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.