Applied AI Researcher, System Self-Construction
Designs self-constructing AI systems that autonomously generate, assemble, and refine subsystems using meta-learning, program synthesis, and evolutionary methods. Requires proven research in modular AI architectures, daily AI tool usage, and strong prototyping skills.
About the job
Key Responsibilities
- Design architectures capable of autonomously generating, assembling, and refining sub-systems.
- Develop meta-learning loops, automated pipeline generation, and self-architecting frameworks that reduce the human bottleneck in complex system creation.
- Study recursive design principles: how systems represent their own construction processes, evaluate them, and evolve.
- Draw from meta-learning, program synthesis, and evolutionary computation to explore self-referential, generative system architectures.
Requirements
- Experience building modular and composable systems (e.g., graph-based planners, agent orchestration frameworks, workflow engines, automated pipeline builders).
- Experience building with models, not just building models: expertise in compound AI systems, agentic collaboration, ensembling, ReAct, graph-of-thoughts.
- Proven track record of research results (publications, public work).
- Uses AI tools daily (e.g., ChatGPT, Cursor, Perplexity).
- Strong programming and data analysis skills for building prototypes and running experiments.
What We Offer
- Base salary: $150K – $250K, depending on experience, location, and level.
- Meaningful equity.
- 100% covered medical, dental, vision; 401(k); commuter benefits, in-office lunch.
- Access to state-of-the-art models and AI tools.
Skills
Meta-Learning, Program Synthesis, Evolutionary Computation, React, Graph-Of-Thoughts, Agentic Collaboration, Compound Ai Systems, Graph-Based Planners, Agent Orchestration, Workflow Engines
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