1234 open jobs
Open roles in AI training, model evaluation, RLHF and data labeling for domain experts. Search, filter, then apply directly on Mercor, micro1, Turing, Ethos, Mindrift, DataAnnotation, Alignerr, Handshake AI, Surge AI, xAI, Vetto or Terac.
AI Training Specialists label, classify, rate, and evaluate AI-generated content across multiple formats to improve AI system accuracy and reliability. This remote, flexible contract role suits detail-oriented individuals committed to quality work on structured AI training tasks.
This role involves designing and optimizing Python-based backend systems for data annotation, validation, and AI model training infrastructure. The position requires a senior full-stack engineer to build high-performance data pipelines, asynchronous task queues, and evaluation systems used by leading AI labs.
This role involves building and optimizing high-performance backend systems and tooling in Rust to support AI data pipelines, annotation workflows, and evaluation systems. You will work on production infrastructure that powers advanced AI model training, collaborating with research and engineering teams on scalable solutions.
Lead a team of business analysts creating high-quality content to train AI models on business strategy, finance, and operations. This role combines team management, quality assurance, and analytical expertise to develop materials that teach AI systems professional reasoning across multiple business domains.
A senior C++ engineer will design and build high-performance data pipelines, annotation tooling, and evaluation infrastructure for AI systems. The role involves optimizing backend services for large-scale data processing and quality control in support of model training and validation.
Design and build high-performance C++ systems for AI data pipelines, evaluation workflows, and internal tooling. This role involves optimizing production codebases, developing backend services for data annotation and quality control, and collaborating with research teams to support model training infrastructure.
This role involves designing and optimizing high-performance C++ systems for AI infrastructure, including data pipelines, annotation tooling, and evaluation workflows. The position is ideal for senior C++ engineers who specialize in performance optimization and want to contribute to cutting-edge AI research infrastructure.
A senior C# engineer will design and build high-performance data pipelines, annotation tooling, and evaluation systems for AI model training. The role involves full-stack backend development, system optimization, and collaboration with data and research teams to support production infrastructure for AI labs.
This role involves annotating and evaluating chemistry content for AI model training. A PhD chemist will label complex chemistry questions, map conceptual relationships, review AI-generated answers, and develop datasets across multiple chemistry subfields to improve frontier AI models.
Cinematography professionals and advanced film students analyze film clips to train AI systems to understand visual storytelling. You will break down camera work, shot composition, framing, and scene structure into detailed, structured annotations that help AI perceive and describe cinema.
This role involves reviewing and annotating electronic health record data to ensure accuracy and consistency for clinical and research applications. The position is ideal for healthcare professionals with experience in clinical documentation, medical coding, or chart review who have strong attention to detail and can work independently on data quality assurance tasks.
This role involves evaluating and improving AI models that process visual data, including images and video. Computer vision and machine learning experts will assess model outputs, identify failure modes, create training annotations, and provide technical feedback to guide the development of AI systems used at scale.
A senior C++ engineer is needed to design and optimize high-performance data pipelines, annotation tooling, and evaluation systems for leading AI research teams. This fully remote contract role involves full-stack development, system optimization, and collaboration with data and research teams on production-grade infrastructure.
Design and build high-performance Rust systems for AI data infrastructure, including data pipelines, annotation tooling, and evaluation systems that support large-scale AI research. This is a fully remote contract role for senior engineers with deep expertise in systems optimization and concurrent programming.
This role involves categorizing, tagging, and annotating text, images, and audio data to train AI systems. Data Labeling Specialists work independently on a flexible remote contract, following structured guidelines to ensure consistent, high-quality dataset preparation for machine learning models.
A senior Python engineer will design and optimize high-performance data pipelines, annotation tooling, and evaluation systems for AI model training at scale. This fully remote contract role requires building full-stack infrastructure that processes large datasets and supports research workflows across distributed teams.
This role involves reading, annotating, and classifying diverse documents to help train AI systems understand written text. Specialists work remotely and flexibly, applying structured annotation frameworks to structured and unstructured content across various industries and topics.
Review, categorize, and refine product data for AI-powered shopping and recommendation systems. This role involves evaluating product listings, AI-generated descriptions, and ensuring data quality to improve product discovery. Ideal for detail-oriented individuals comfortable with online platforms and structured data.
This role involves annotating clinical data from Electronic Health Records to train AI systems. Clinically knowledgeable professionals will review and label medical information including diagnoses, procedures, and clinical notes to improve AI understanding of healthcare data.
This remote contract role asks experienced full-stack developers to review and evaluate code and system designs produced by AI models. The work also includes building tooling for data annotation and quality control, done asynchronously on a flexible schedule. It suits engineers with several years of production experience who can give precise technical feedback.
FAQ
AI training, model evaluation, RLHF, red teaming, data labeling and expert review roles, in fields from software and data science to medicine, law, finance, languages and science.
They are done online. Some are limited to residents of certain countries: when the platform publishes that restriction, the listing shows it.
Usually not. Most roles ask for professional experience in your own field. Each listing states the experience the platform requires.
By the hour or by the task, by the platform that hires you. We show the pay only when the platform publishes it. It is not a guarantee of income or hours.
Apply now opens the official posting on Mercor, micro1, Turing, Ethos, Mindrift, DataAnnotation, Alignerr, Handshake AI, Surge AI, xAI, Vetto or Terac, where you complete the application. You need no account here. See how it works.
