Conducts applied research on long-horizon autonomous AI agents, focusing on evaluation, post-training, environment design, and benchmarks to improve frontier models. Builds simulations, runs experiments, ships production code, and publishes findings.
200k – 350k
On-siteAI Research
About the role
Responsibilities
Advance the frontier of autonomous agents through core research in long-horizon evaluation, agent post-training, and environment design.
Understand where current models fail and how to improve them.
Build benchmarks, create environments, write production code, and run rigorous experiments.
Develop advanced environment simulation engines for training & evaluating autonomous AI agents.
Investigate failure modes of frontier models.
Create rigorous benchmarks for complex, realistic tasks requiring long-horizon reasoning and tool use in dynamic environments.
Post-training agents in complex simulation environments.
Publish research.
Requirements
Strong engineering & research fundamentals and prolific user of AI tools.
Leads research in computer vision, multimodal understanding, and visual generation. Develops novel models and methodologies, translates research to production, and mentors teams. Requires PhD preferred, 8+ years experience, and expertise in PyTorch, TensorFlow, transformers.
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