---
title: 'AI Researcher at AGI, Inc.'
canonical: 'https://feeny.ai/job/ai-researcher-agi-inc-san-francisco-3yc662yahsp8'
type: 'job'
last_seen: '2026-09-10'
---

# AI Researcher at AGI, Inc.

- **Company:** AGI, Inc.
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-08-16
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/agi-inc/792da3fd-c1ae-4e06-9398-f40092f1d612

## Job description

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](https://drive.google.com/file/d/1ZydjdMeMh3x-QItUPQFbJUbhBW-4-XHa/view?usp=sharing))

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

Make devices think like a frontier model. Frontier capability inside the compute and memory envelope of a consumer device — phone, laptop, wearable — is not a constraint. It's the most interesting research problem in applied AI today. You'll lead training for one of the model families that powers our on-device agents: pretraining recipe choices, post-training (SFT, RLHF, DPO, GRPO and whatever the next acronym ends up being), distillation, quantization, and the long tail of tricks that make a small model punch above its weight. This is for the researcher who's tired of training models that go behind an API. You want your model on the device in your pocket, your mom's pocket, and a hundred million pockets you'll never meet.

🤩 Tasks you will own

- One or more model capabilities end-to-end — from data mixture and training objective through eval and shipping into a production on-device runtime
- The experiment design and writeups that compound across the team — kill what doesn't move the metric, double down on what does
- A training workstream with a clear success metric and a checkpoint that ships

🤚 Areas where you will assist

- Infra and product engineers, by turning research wins into shipped capabilities
- Partnerships, by telling them honestly what's possible at the next device refresh and what's not
- Other researchers, by reading their code and making theirs easier to read

📚 Skills you'll be expected to teach

- The training techniques that matter most for our regime — distillation from frontier teachers, MoE at small scale, speculative decoding, KV cache compression
- How to design experiments that move a number you actually care about

🧑‍🎓 Skills you'll be expected to learn

- What production model deployment looks like under hardware deadlines from OEM partners
- On-device tool use and agentic post-training at consumer scale
- The full stack from training run to phone

-

🏆 Timeline of success After 30 days — You've reproduced one of our recent training runs end-to-end. You've named the three highest-leverage research bets for the next quarter and have a take on which two to run. After 60 days — You're leading a training workstream with a clear metric. You've shipped a checkpoint that beats the previous best on the eval that matters. People trust your read on what's working. After 90 days — Your work has shipped into a partner build. You've made one non-obvious bet that paid off and one that didn't, and the team has learned from both. You're shaping the next training cycle.

💰 Compensation Competitive cash and meaningful equity. Top-tier relocation and immigration support. Permission to publish what's safe to publish. SF, in person.

How to apply Send a link to your most interesting result — paper, blog, model card, GitHub — with one paragraph on why it matters. Plus your resume, Google Scholar, or LinkedIn. Every exceptional candidate hears back within 48 hours.

## About AGI, Inc.

## Company Overview
- **One-liner**: AGI, Inc. is an applied AI lab bringing superintelligence to the edge by building fully agentic, on-device AI that runs locally without cloud dependencies.
- **Entity Type**: Private (Seed stage – $20M raised)
- **Headquarters**: San Francisco, California, United States (also offices in India, Japan, Brazil)
- **Founded**: 2025
- **Founders**: Div Garg (CEO; co-founder background inferred from leadership), Steve Frey (Cofounder, Product)

## Core Business
- **Primary industry/industries**: Agentic AI / On-device Artificial Intelligence / Edge Computing
- **Target customers**: B2C (individuals using mobile devices) and B2B (partnerships with hardware makers like Qualcomm, Lenovo, Visa for agentic commerce)
- **Mission/purpose statement**: “Bring genuinely useful AGI into everyday life” – making superintelligence 100% secure, private, and accessible on the devices people already own.

## Products & Services
- **[AGI-0]**: A mobile-use agent that proactively handles tasks (booking taxis, ordering food, replying to messages, finding flights) by operating a user’s apps locally and personally. Fully agentic, no cloud round-trips.
- **[On-Device Foundation Models]**: AGI, Inc. runs its own foundation models on-device, enabling agents that act rather than just answer. Up to 96% faster processing-near-memory without hardware changes.
- **[Research & Developer Tools]**: Offers a blog, deeplearning.ai courses, and an evaluation framework for web AI agents.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private)
- **Key Metric**: Total funding $20M (Seed round, September 2025, led by 11 investors including Techstars, individual angels)
- **Notable Investors/Partners**: Qualcomm Technologies (collaboration to bring agentic AI to Snapdragon-powered devices), Visa (transforming agentic commerce), Lenovo (proof-of-concept integration demonstrated at MWC), Anand V Lalwani (angel)
- **Growth Signals**: 26 employees, monthly headcount growth +4.3%, LinkedIn followers 22,530 (+3.5% monthly), 6 active job postings (+50% quarterly). Demonstrated prototype at MWC (March 2026) and a research preview released in October 2025. Monthly website visits ~38,700.

## Competitive Advantages
- **True On-Device AI**: No cloud round-trips – all data stays on the device, ensuring privacy, security, and low latency. Differentiates from cloud-dependent assistants.
- **Full Agentic Capability**: Agents act proactively on the user’s behalf, not just answer queries. Integrated with phone apps similarly to a human user.
- **Hardware Partnerships**: Early collaborations with Qualcomm (Snapdragon), Lenovo, and Visa give route-to-market and credibility.
- **Processing-Near-Memory Innovation**: Claims 96% faster processing without hardware changes, a significant efficiency moat.

## Strategic Focus
- **Current priorities**: Scaling the on-device agent platform, deepening hardware partnerships (Qualcomm, Lenovo), expanding agentic commerce (Visa), and hiring top AI/engineering talent. Growing presence in US, India, Japan, Brazil.
- **Direction for growth**: Deploy “superintelligence in your hands” to billions of devices – moving AI from data centers to pockets, driveways, and living rooms.

## Why Work Here
- **Culture**: Described as a place for “passionate builders, innovators, and dreamers”. High-impact mission to bring AGI to everyday life. Employee rating on LinkedIn 5.0/5.0 (1 review) – strong marks for work-life, compensation, culture, career.
- **Remote/hybrid/office**: Presence in San Francisco (HQ plus two other office locations), with additional team members in India, Japan, Brazil. Likely a flexible or hybrid model given global distribution.
- **Notable perks/engineering culture**: Flat structure with 26 employees; department breakdown shows technical roles (12%) and product (6%) plus research. Open positions: AI Researcher, ML Platform Engineer, iOS Engineer, Backend Engineer, Product Designer – indicating strong engineering and research focus.
- **Growth trajectory**: Early-stage startup with $20M funding and rapid hiring (+50% job postings quarterly). Opportunity to shape foundational AI product from early days.

## Sources
1. [theagi.company](https://theagi.company/)
2. [linkedin.com](https://www.linkedin.com/company/the-agi-company)
3. [theagi.company/build](https://www.theagi.company/build)
4. [jobs.ashbyhq.com/agi-inc/792da3fd-c1ae-4e06-9398-f40092f1d612](https://jobs.ashbyhq.com/agi-inc/792da3fd-c1ae-4e06-9398-f40092f1d612)
5. [jobs.ashbyhq.com/agi-inc/442fee6d-2c44-4a2d-9daa-d209a22a14d5](https://jobs.ashbyhq.com/agi-inc/442fee6d-2c44-4a2d-9daa-d209a22a14d5)

## Other roles at AGI, Inc.

- [iOS Engineer](https://feeny.ai/job/ios-engineer-agi-inc-san-francisco-t1e8e58hm2yc) — San Francisco, CA
- [Research Engineer - Evals](https://feeny.ai/job/research-engineer-evals-agi-inc-san-francisco-h3fm9b42ytfx) — San Francisco, CA
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- [Product Designer](https://feeny.ai/job/product-designer-agi-inc-san-francisco-qfhz9cmpca8z) — San Francisco, CA
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