Join the Ensemble

Lead original research into practice-based learning and deliberate practice for AI agents. You'll design experiments that probe how agents improve through structured repetition and self-assessment, publish findings at top venues, and help define our core research agenda.

Requirements: PhD or equivalent research experience in ML/AI; publications at NeurIPS, ICML, ICLR, or ACL; deep interest in agent learning, evaluation methodology, and skill acquisition; strong Python and experiment-design fundamentals.

Build the infrastructure that makes agent training loops possible. You'll design feedback pipelines, experiment orchestration systems, and the scaffolding that lets agents practice, fail, and improve at scale — the engineering backbone of our core research.

Requirements: Strong software engineering fundamentals; hands-on experience building or evaluating LLM-based agents; proficiency in Python and modern ML frameworks; comfort shipping production-quality systems alongside research prototypes.

Own the evaluation infrastructure and developer-facing APIs that the community depends on. You'll build scalable systems for large-scale model evaluation, design reliable data pipelines, and ship the open-source tooling that makes rigorous AI benchmarking accessible to everyone.

Requirements: 5+ years in backend or platform engineering; experience with distributed systems and cloud infrastructure (AWS/GCP); track record of building and maintaining well-documented open-source projects; Go, Rust, or Python at production scale.

Take practice-based agents from research into enterprise deployments. You'll work directly with customers to understand their workflows, adapt our agent systems to real-world constraints, and close the loop between production feedback and the research team.

Requirements: Experience deploying ML systems to production; familiarity with LLM fine-tuning, RLHF, or agent frameworks; strong Python engineering skills; comfort navigating ambiguous customer requirements and translating them into technical specs.

Shape how people interact with AI agents. You'll design interfaces for agent monitoring, feedback collection, and practice-loop visualization — making complex agent behaviour legible and actionable for researchers and end users alike.

Requirements: 3+ years of product or interaction design; experience designing developer tools or data-heavy interfaces; strong Figma skills; genuine curiosity about AI agent behaviour and how to surface it clearly; bonus: experience with ML or research tooling.

Be the voice of Etude AI in the open-source community. You'll write the documentation, tutorials, and blog posts that help developers understand and use our tools; engage with community contributors on GitHub; and help us tell the story of what we're building and why it matters.

Requirements: Proven track record of technical writing for developer audiences; comfort reading and writing Python; experience growing open-source communities or developer advocacy programs; strong editorial instincts and the ability to explain hard ideas clearly.