Handshake AI is seeking a PhD Student Researcher to work on novel RLHF/GRPO pipelines, instruction-following refinements, reasoning-trace supervision, multilingual/long-horizon/domain-specific benchmarks, automatic vs. human preference studies, robustness diagnostics, active-learning loops, data value estimation, synthetic data generation, and low-resource fine-tuning strategies. The goal is to produce an archive-ready manuscript or top-tier conference submission.

Senior Engineering Manager to lead the Reinforcement Learning Environments (RLE) team, responsible for building interactive sandboxes that simulate end-to-end workflows for frontier models. The team generates high-signal interaction data used for training and evaluating models on task completion, quality, and robustness. The role involves leading a team of engineers, owning the RLE roadmap, driving architecture for scalable systems, and ensuring reliability and data quality.

Physics PhDs are needed to evaluate AI-generated content and provide feedback to improve AI's understanding of physics reasoning, proof construction, and technical problem-solving. This is a flexible, hourly contract role.

This role involves Mathematics PhDs evaluating AI-generated content and providing feedback to improve AI's understanding of mathematical reasoning. It's a flexible, hourly contract position focused on content review rather than traditional AI development.

This role involves evaluating AI-generated music content and providing feedback to improve AI understanding of music production workflows. It requires hands-on experience with LMMS and music composition, with no prior AI technical experience needed. The work is project-based, hourly, and remote within the USA, suitable for independent contractors.

This role involves evaluating AI-generated music content and providing feedback to improve AI models, leveraging experience with LMMS and music production concepts. It's a contract role focused on data annotation and quality assessment for AI training.