Handshake

Your insights will directly contribute to the training of AI in chemistry, physics, and engineering applications. You’ll help AI better understand structure-property relationships, materials design, and experimental methods. You will review AI-labeled content across materials science and engineering topics, assess accuracy and completeness of data and support the development of AI tools used in research and applied science.

Contribute to building AI that understands climate data, sustainability topics, and ecological systems, ensuring that AI outputs in environmental contexts are scientifically sound and data-driven. Evaluate environmental science-related content and feedback from AI trainers, aligning it with real-world scientific principles and data. Provide expert input on climate science, ecosystems, and policy-oriented topics, working with cross-functional teams to enhance annotation tools.

Evaluate expert-labeled data using proprietary tools to help shape the next generation of AI systems. Use your domain expertise in biology, neuroscience, or related fields to ensure scientific accuracy and quality in AI training by providing structured feedback and assessing human and AI-generated scientific responses.

As an AI Tutor specializing in Chemical Engineering, you will help advance the development of AI systems by reviewing and evaluating expert-labeled data related to thermodynamics, process systems, transport phenomena, and chemical reactions. Your domain expertise ensures that AI outputs reflect rigorous scientific and engineering principles.

Provide payments, contracts, and general support to Handshake MOVE Fellows. Working with Handshake AI Ops, Finance, Product, Engineering, Projects and Support teams to provide efficient support, and improve fellows customer experience. Focus primarily on handling payment questions, disputes, and managing contracts.

Help refine the understanding and accuracy of AI models by reviewing and correcting outputs in topics spanning electrical circuits, signal processing, embedded systems, power systems, and electromagnetics. Your domain knowledge will help AI systems better interpret and respond to complex engineering queries with technical precision. This is a contract remote position with variable time commitments.

Evaluate, debug, and improve AI-generated code in a variety of programming languages. Ensure code quality meets best practices for readability, performance, scalability, and correctness. Curate coding problems, write clean reference implementations, and annotate model outputs. Develop clear technical documentation to help models learn and replicate expert coding approaches.

Advance AI capabilities by reviewing expert-annotated biological data using proprietary software. Your expertise in biology will directly contribute to the training of AI models, ensuring accuracy in biological concepts, terminology, and applications. This role requires analytical thinking, adaptability, and a passion for technological innovation in the life sciences.

Shape the next generation of AI models by reviewing and enhancing outputs generated by cutting-edge large language models (LLMs). Your expertise in statistics, data analysis, and quantitative reasoning will ensure that model outputs are accurate and insightful. This role blends technical fluency with high-precision annotation and offers the opportunity to influence how AI understands and communicates statistical concepts.

Evaluate AI-generated educational content and provide expert feedback on pedagogy, structure, and clarity. This role involves scoring and critiquing model outputs related to tutoring, instructional design, and assessment across K–12, higher ed, and lifelong learning domains. Collaborate with cross-functional teams to develop annotation standards and quality criteria for educational data.

Evaluate AI-generated musical content for accuracy, creativity, musicality, and genre/style adherence. Use internal tools to score, annotate, and critique examples across a variety of musical formats and tasks. Provide expert feedback on structure, harmony, orchestration, and production quality. Help curate, refine, or author musical examples across multiple genres and traditions to support training datasets.