Founding Engineer, Research

Cua is building infrastructure for safely and scalably running general AI agents on real computers and apps.

With 9k+ GitHub stars in just 4 months and backing from Y Combinator, we’re advancing agentic AI from research to production.

We’re hiring a Research Engineer to help develop and scale advanced multi-modal AI agents — working across model training, agent benchmarking, and real-world deployment.

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WHAT YOU’LL DO

You’ll sit at the intersection of applied research and engineering, helping us build, evaluate, and ship the next generation of generative agent systems.

Example work includes:

•	Designing and running experiments on commercial/open-source LLMs (e.g., OpenAI, LLaMA, Qwen)

•	Building scalable pipelines for training, fine-tuning, and evaluating multi-modal agents

•	Developing tools and benchmarks to test agent reasoning, control, and performance

•	Improving infrastructure for deploying agentic AI models across OS environments

•	Supporting research-to-production workflows for internal and external users

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WHAT WE’RE LOOKING FOR

•	Strong experience with generative AI, LLMs, and agentic systems

•	Hands-on with commercial and open-source models at scale

•	Proficiency in Python and PyTorch (C++/Java a plus)

•	Experience with data curation pipelines and multi-modal training workflows

•	Comfortable designing experiments, testing infra, and pushing code into prod

•	Exposure to cloud compute (AWS/GCP), APIs, structured/unstructured data

•	Open-source or competition experience is a plus

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LOGISTICS

•	Full-time, remote-friendly (SF-based team preferred)

•	Role blends fast-paced engineering with cutting-edge research

•	Work used by thousands of developers building with Cua

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APPLY

•	CV + GitHub or portfolio

•	Short note on a project or experiment you’ve recently led

🌐 trycua.com

We’re committed to building a diverse, inclusive team — all backgrounds welcome.