PhD Resident

How you will make 10x impact:

We are building an early-stage moonshot that bridges the gap between foundational models and real-world industrial systems. We aren’t just wrapper-engineering or tweaking prompts; we are designing autonomous agentic platforms capable of modeling physics, writing complex simulation code, and structuring deep domain knowledge.

As an AI Resident, you will work directly with our core architecture team to build systems where AI doesn't just output text, but actively interprets, maps, and simulates the physical world.

• Design Agentic Frameworks: Develop and scale multi-agent platforms that autonomously generate, test, and execute simulation code for complex physical, mechanical, or chemical systems.
• Architect Knowledge Ontologies: Build the formal schemas, data structures, and physical ontologies that allow LLMs to reason accurately about machinery, physical constraints, and engineering primitives.
• Close the Loop on Simulation: Integrate agentic code generation with active physics engines. You'll build the runtime verification and feedback loops that allow agents to self-correct when their simulation code fails.
• Engage with the Community: Embedded directly within a confidential X project, you will collaborate with the broader X intern and AI community, participating in technical colloquia and talks with AI leaders.

This project aims to push the limits of science and modeling as we know them and to prove how ML can radically accelerate our understanding of the world

• Location: X's headquarters in Mountain View, CA
• Start Date(s): Year-round rolling basis
• Duration: a flexible 4 mo. to 1 year program based on project team needs and your availability

Throughout your AI Residency you can expect:

• To be embedded into one of our confidential or public X projects
• To get paid competitively and receive benefits
• To be a part of a lively community of AI and ML Residents
• To attend tech-talks with AI leaders from across X

What you should have:

• PhD Candidate in STEM: Currently enrolled in a PhD program (Computer Science, Physics, Engineering, Math/Stats) with a strong publication or research footprint in ML and excellent general-purpose programming skills.
• Agentic Systems Experience: Hands-on experience building LLM systems that use multi-agent coordination, advanced tool execution, and complex context management. You should deeply understand how state-of-the-art coding agents (e.g., Claude Code, Gemini CLI, Codex) operate under the hood.
• Ontologies & Knowledge Representation: A strong grasp of how to translate physical concepts, engineering rules, or hardware constraints into structured schemas and relational graphs that LLMs can reliably parse and act upon.
• Simulation & Physical Modeling: Experience working with physical applications, hardware logic, or modeling real-world environments where code interfaces directly with physical variables.

It’d be great if you also had these:

• Open-source contributions or peer-reviewed publications at top-tier venues (NeurIPS, ICML, ICLR, CVPR, etc.).
• Experience building deterministic verification loops or execution environments where LLM agents learn from runtime errors.
• Familiarity with physics engines, robotics simulators (e.g., MuJoCo, PyBullet, Gazebo), or CAD APIs to build digital twins and representations of physical machinery.

Additional public information:

https://www.wired.com/video/watch/astro-teller-captain-of-moonshots-at-x-speaks-at-wired25

https://www.bloomberg.com/news/videos/2019-10-10/alphabet-x-s-astro-teller-on-bloomberg-studio-1-0-video

The US base salary range for this position is $109,000 - $157,000 + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include benefits.