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AGI, Inc.

Posted 10 months ago

Open

AI Researcher

San FranciscoOn-siteFull-time

AI Summary

AI researcher role focused on developing novel agentic AI algorithms, running live experiments, and producing production-grade capabilities that blend research with consumer-facing products.

About this role

Think Different. Build the Future. 🚀

Our Mission

Build everyday AGI. Trustworthy, consumer-grade agents that redefine human–AI collaboration for millions. Software shouldn’t wait for commands; it should partner with you, amplifying what you can do every single day.

Why AGI, Inc.

We’re a stealth team of elite founders and AI researchers, with backgrounds spanning Stanford, OpenAI, and DeepMind. We’re industry leaders in mobile and computer-use agents, bringing these capabilities to consumer scale.

Grounded in years of agent research, our AI is designed with trustworthiness and reliability as core pillars, not afterthoughts.

We are supported by tier-1 investors who funded the first generation of AI giants; now they’re backing us to build the next: everyday AGI. (Watch the demo)

If you see possibility where others see limits, read on.

About the Role

You'll be at the forefront of developing novel AI algorithms and techniques for action-taking agentic AI. You will turn bold hypotheses into production-grade capabilities and push the boundaries of what current agents can accomplish.

This is not a pure research role. You'll run live A/Bs on billions of real trajectories and see your ideas land in production within weeks. You'll pair with product engineers to fuse novel algorithms with delightful consumer experiences.

You'll focus on breakthroughs, rigor, and impact — ensuring every experiment moves us closer to trustworthy everyday AGI.

What You'll Do

Push frontiers: Prototype new architectures in reasoning, long-horizon planning, memory, multi-agent coordination and alignment.

Ship, don't shelve: Run live A/Bs on billions of real trajectories and see your ideas land in production within weeks.

Bridge theory and delight: Pair with product engineers to fuse novel algorithms with delightful consumer experiences.

Define the bar: Establish our research rigor, safety metrics, and evaluation pipelines for everything that calls itself "agent-level."

Mentor and magnify: Level up interns, residents, and mixed-discipline hackers, multiplying the impact of the entire team.

Minimum Qualifications

  • PhD or equivalent track record in ML / NLP / RL / systems

  • 3+ strong papers or significant open-source impact

  • Mastery of PyTorch or JAX

  • Experience with large-scale training across distributed GPU clusters

  • Strong programming skills and ability to ship production code

Preferred Qualifications

  • Publications at top-tier ML conferences (NeurIPS, ICML, ICLR, ACL)

  • Hacker mindset — equally happy debugging HTML selectors and re-deriving state-space math

  • Experience with RLHF, alignment, or agent-based systems

  • Track record of research that shipped to production

  • Passion for shipping to real users, not just writing PDFs

Why This Role Matters

Great research without great product is a paper. Great product without great research hits a ceiling.

You will define what's possible for agentic AI, and your work will directly shape how millions of people experience autonomous collaboration.

Our Culture

🏢 All in, in person — work moves faster face-to-face
🚀 Ship by default — speed and polish can coexist
🤝 One band, one sound — radical candor, zero politics

Perks

🏥 Competitive company-sponsored medical, dental, and vision insurance
✈️ Top-tier relocation and immigration support

How to Apply

Send us:

  • A link — or 60-second video — of something you built and why it matters

  • Your resume or LinkedIn

  • Two sentences on the hardest problem you've cracked

Every exceptional candidate hears back within 48 hours.

If you see possibility where others see limits, we'd love to meet you.

Skills

Agent-based SystemsAlignmentDistributed GPU TrainingEvaluation PipelinesExperimentation PipelinesJAXMachine LearningMemory ArchitecturesMulti-agent CoordinationNatural Language ProcessingNeurIPS ICML ICLR ACL PublicationsPlanningProduction CodePyTorchReinforcement LearningRLHFSystems Programming

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