Stealth Startup(Augmented to Real Intelligence Deep Research) Zero-to-One AI/Data Science Researcher

Qualifications

• ✔ Translate research into systems: Turn experiments into scalable, usable intelligence products
• A data scientist, AI researcher, or ML engineer with strong research instincts
• Deeply interested in reasoning, intelligence, cognition, and research automation
• Comfortable working without predefined answers or clean datasets
• Experienced in experimentation, evaluation, and iteration
• Thinks in frameworks, not just code
• Curious about how intelligence actually works, not just how to prompt models
• Values originality, rigor, and first-principles thinking
• 🔹 AI Research & Experimentation: Design and test intelligence and reasoning architectures
• 🔹 Data Science & Evaluation: Develop metrics for intelligence quality, reasoning depth, and research validity
• You enjoy deep research problems more than polished dashboards
• You want to explore how AI can reason, research, and synthesize knowledge
• You’re excited by long-term, high-impact research over quick wins

Responsibilities

• You will lead the research and experimentation required to move from augmented AI tools to real, reasoning-driven intelligence systems
• Your work will focus on designing systems that:
• Conduct multi-step research autonomously
• Reason across noisy, incomplete, or conflicting data
• Synthesize knowledge, not just retrieve it
• Improve through feedback, validation, and iteration
• You will operate at the frontier of applied AI research, blending theory, experimentation, and product-driven thinking
• ✔ Build zero-to-one intelligence systems: From research pipelines to reasoning architectures
• ✔ Design deep research workflows: Multi-source ingestion, validation, synthesis, and insight generation
• ✔ Experiment with advanced models: LLMs, agents, retrieval systems, reasoning frameworks, and hybrid approaches
• 🔹 System Design: Build pipelines that combine retrieval, reasoning, synthesis, and feedback loops
• 🔹 Model & Agent Development: Experiment with agents, tools, memory, and long-context systems
• You will function at a co-founder-level research capacity, with ownership in the systems and breakthroughs we create

Full Description

About the JobAbout Us

Tunjio Labs is a forward-thinking stealth research startup focused on advancing Augmented Intelligence into Real Intelligence.

We are building deep research systems that move beyond surface-level AI outputs toward reasoning, synthesis, verification, and insight generation at a human-expert level.

Our work sits at the intersection of AI research, data science, cognitive systems, and applied intelligence.

We are not chasing hype.

We are building foundational intelligence systems designed to think, research, validate, and evolve.

We are seeking a Zero-to-One AI/Data Science Researcher — not just a model builder, but a research co-founder who can help turn ambitious intelligence ideas into working systems.

This is not a traditional job.

This is an opportunity to co-build a deep-tech intelligence company with equity-based compensation.

Role Overview

We are looking for a Zero-to-One AI/Data Science Researcher who thrives in ambiguity and deep problem-solving.

You will lead the research and experimentation required to move from augmented AI tools to real, reasoning-driven intelligence systems.

Your work will focus on designing systems that:

• Conduct multi-step research autonomously

• Reason across noisy, incomplete, or conflicting data

• Synthesize knowledge, not just retrieve it

• Improve through feedback, validation, and iteration

You will operate at the frontier of applied AI research, blending theory, experimentation, and product-driven thinking.

You Will

✔ Define the research direction: What does “Real Intelligence” mean in practice, and how do we measure it?

✔ Build zero-to-one intelligence systems: From research pipelines to reasoning architectures.

✔ Design deep research workflows: Multi-source ingestion, validation, synthesis, and insight generation.

✔ Experiment with advanced models: LLMs, agents, retrieval systems, reasoning frameworks, and hybrid approaches.

✔ Translate research into systems: Turn experiments into scalable, usable intelligence products.

Who You Are

• A data scientist, AI researcher, or ML engineer with strong research instincts.

• Deeply interested in reasoning, intelligence, cognition, and research automation.

• Comfortable working without predefined answers or clean datasets.

• Experienced in experimentation, evaluation, and iteration.

• Thinks in frameworks, not just code.

• Curious about how intelligence actually works, not just how to prompt models.

• Values originality, rigor, and first-principles thinking.

Key Responsibilities

🔹 AI Research & Experimentation: Design and test intelligence and reasoning architectures.

🔹 Data Science & Evaluation: Develop metrics for intelligence quality, reasoning depth, and research validity.

🔹 System Design: Build pipelines that combine retrieval, reasoning, synthesis, and feedback loops.

🔹 Model & Agent Development: Experiment with agents, tools, memory, and long-context systems.

🔹 Collaboration: Work closely with founders to shape the company’s long-term research vision.

Compensation

This is an equity-based role.

You will function at a co-founder-level research capacity, with ownership in the systems and breakthroughs we create.

Who This Role Is For

• You’re frustrated by shallow AI demos and want to build real intelligence.

• You enjoy deep research problems more than polished dashboards.

• You want to explore how AI can reason, research, and synthesize knowledge.

• You’re excited by long-term, high-impact research over quick wins.

• You want to help define what the next generation of intelligence systems looks like.

If you’re ready to push AI from augmentation to real intelligence, let’s talk