AI Engineer Intern
San Francisco, CA at a glance
- Rent
- #2 of 51$2,680/mo+46% vs US avg
- Weather
- #17 of 51295 mild days0 hot · 0 cold
- Income tax
- #1 of 5113.3% top rateCalifornia
What you need
- LLMs, modern AI frameworks, or ML experience
- Prompt engineering strategies experience
- Strong Python and TypeScript foundation
What you'll do
- Build browser agent and tool-calling systems
- Build evaluation frameworks for agent performance
- Build memory and personalization layer for workflows
Join us in pushing the boundaries of what's possible with LLMs and browser-native AI. You'll work on cutting-edge problems in agent systems, context handling, and tool use, while collaborating directly with our research team to bring novel approaches to production.
What You'll Build
- Browser agent and tool-calling systems.
- Evaluation frameworks for agent performance.
- Memory and personalization layer for workflows
Requirements
- Research/work experience with LLMs, modern AI frameworks, and/or ML.
- Experience with prompt engineering strategies.
- Strong foundation in Python and TypeScript.
Sample Projects
- Agentic systems that predict and execute users’ next steps in complex workflows.
- A searchable, self-updating memory store for personalized browser agent behaviour.
- Designing intuitive interfaces for how users should delegate and override AI actions.
- A system to interpret DOM snapshots, mouse click events, and keyboard inputs to select browser actions.
- A context composer that feeds relevant info into LLM prompts based on user interactions, page content, and memory.
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About Thirdlayer
ThirdLayer is the learning and alignment layer for enterprise AI. We continuously ingest and structure messy organizational context, complex operational processes, and siloed, permission-sensitive data, then grade agents against the outcomes each company cares about. Every interaction becomes feedback that helps agents improve over time. Companies use ThirdLayer to power their internal agents or embed it into the AI products they’re building. We give agents the context, evaluations, and learning loops they need to stay aligned with each organization and deliver better outcomes with every run.
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