Selected physicians will test a healthcare technology product by following predefined clinical workflows and tasks. They are responsible for providing structured feedback on usability, functionality, and clinical relevance to identify potential improvements.
Physicians will test a new healthcare technology product by following predefined clinical workflows and tasks. They are responsible for providing structured feedback on usability, functionality, and clinical relevance to help improve the product.
Own end-to-end production of software-engineering data and evaluation programs, managing contributors, quality, throughput, costs, timelines, and delivery recovery. Review code and related artifacts for technical correctness, improve task and review processes, and communicate progress, risks, and corrective actions to customers and internal teams.
Participate in natural, unscripted group conversations on assigned topics to support multi-speaker diarization projects. Ensure active contribution by responding to others, asking questions, and maintaining a natural conversational flow.
Participate in natural, unscripted group conversations on assigned topics to support multi-speaker diarization projects. Ensure active contribution by responding to others, asking questions, and maintaining a natural conversational flow.
Participate in multi-speaker diarization sessions by engaging in natural, unscripted group conversations on assigned topics. Maintain an interactive discussion while ensuring clear, high-quality audio recording in a quiet environment.
Participate in multi-speaker diarization projects by engaging in natural, unscripted group conversations on assigned topics. Ensure clear, interactive communication while maintaining a professional recording environment.
Participate in multi-speaker diarization projects by engaging in natural, unscripted group conversations on assigned topics. Ensure active contribution to discussions while maintaining clear, natural speech and following specific recording environment guidelines.
Select and review archived footage to ensure it meets the project requirements, then submit a sample and upload accepted footage through a secure link. Retain raw files for possible review and ensure the footage and identifiable people are properly cleared for licensing.
Lead and mentor a pod of technical trainers to develop and review realistic, terminal-based scientific and engineering tasks for AI training. Ensure all tasks are scientifically accurate, reproducible, and meet high-quality standards for frontier AI evaluation.
Lead and mentor a pod of technical trainers to develop and validate realistic, terminal-based scientific and engineering tasks for AI training. Ensure all tasks are reproducible, scientifically accurate, and meet high-quality standards for frontier AI evaluation.
Create stylized illustrations while maintaining visual consistency and adapting to multiple artistic styles. Document metadata and collaborate with teams to ensure final outputs are polished and production-ready.
The role involves researching niche topics to create benchmark tasks that expose weaknesses in state-of-the-art AI models. You will also be responsible for verifying facts, testing models, and diagnosing the root causes of AI reasoning failures.
Create high-quality stylized 3D models and digital assets using various styles and material-driven techniques. Document workflows, incorporate feedback, and optimize assets for production.
Review screen-recorded Adobe Premiere Pro workflows to ensure they meet professional standards and project guidelines. Provide clear, constructive written feedback to contributors and log review outcomes in the project tracker.
Research frontier AI systems and develop datasets, experiments, prototypes, tools, and evaluation frameworks across areas such as reinforcement learning, post-training, synthetic data, and AI agents. Analyze results rigorously and collaborate across teams to turn validated research into scalable products and share findings with the research community.
Lead end-to-end delivery of large-scale multimodal AI annotation projects, managing scope, resources, timelines, budgets, clients, and stakeholder communication. Lead and mentor Team Leads, partner with Quality Managers, monitor performance and quality metrics, address risks, and scale teams and processes as needed.
Lead QA teams across shifts and manage quality operations for multimodal AI annotation projects, including review priorities, sampling, audits, calibration, and performance tracking. Investigate quality issues, drive corrective actions, document guideline decisions, share delivery insights, and report results to the Quality Manager.
Lead annotators and Pod Leads in managing annotation batches from launch through delivery, setting targets, maintaining staffing, and monitoring productivity and quality. Coach and retrain team members, collaborate with QA and tooling teams to improve processes, develop future leaders, and report progress, risks, and blockers to the Project Lead.
The Quality Lead will manage review queues and oversee QA reviewers to ensure the accuracy and consistency of annotated data. They are responsible for providing actionable feedback, tracking performance metrics, and training new team members on guidelines and tools.
Plan and deploy resources across a large-scale AI training program, aligning contributor capacity with client demand and monitoring utilization, throughput, and operational risks. Maintain and improve resource tracking systems, lead process improvements, coordinate with stakeholders, and manage Supply Coordinators to support continuous operations.
Allocate and redeploy contributors across AI training projects, coordinating access, training, instructions, and resource requests. Maintain workforce and capacity data, monitor project throughput and onboarding, escalate risks or data issues, and communicate pending actions across shifts.
Design challenging, realistic agentic scientific workflows that require AI agents to independently navigate data, execute code, and troubleshoot complex tasks. Ensure all tasks are reproducible, self-contained, and objectively verifiable within a controlled computational environment.
The Student Project Ambassador is responsible for recruiting university students to participate in an AI video collection project. They will manage community outreach, track referral progress, and provide guidance to candidates throughout the application process.
The role involves analyzing complex datasets and research-based questions to improve the performance of large language models. Responsibilities include summarizing content, validating information accuracy, and creating training scenarios to enhance model responses.
Design challenging, agentic genomics tasks and reference solutions for AI model evaluation. Develop reproducible scientific workflows and robust grading criteria to assess AI performance on complex biological data analysis.
The role involves reviewing AI-generated medical text and images for dermatological accuracy, safety, and completeness. You will provide expert feedback to improve the medical integrity of LLM outputs and collaborate with researchers to align model performance with clinical standards.
Review AI-generated medical text and images for dermatological accuracy, safety, and clinical completeness. Collaborate with researchers to align model performance with evidence-based dermatology standards.
Create original research tasks that evaluate AI systems by synthesizing clues from reputable open web sources. Document definitive answers, verify all sources, and refine tasks based on model performance and reviewer feedback.
Review AI conversations to evaluate context gathering and provide structured feedback to improve conversational quality. Collaborate with research teams to ensure consistent assessments and identify missed opportunities for clarification.
