
Leading edge research, proprietary models and agents, and a forward-deployed implementation approach for tangible ROI

Leading edge research, proprietary models and agents, and a forward-deployed implementation approach for tangible ROI
Founded: 2024 (Paris)
Core focus: Agentic AI systems and developer-facing products for automating web and enterprise workflows
Notable funding: $220M seed round (May 2024)
Offices / presence: Paris, London, New York
Employee count (snapshot): 326
Automation of web and enterprise workflows via agentic/autonomous AI agents and developer APIs.
2024
Artificial Intelligence / Enterprise software
$220M
Reported as a mix of equity and convertible debt; some reporting cites ~ $230M when including convertible notes
“Backed by a mix of venture funds, strategic corporate partners and notable individuals including Accel, Creandum, Bpifrance, Amazon/AWS, Samsung, UiPath, Eric Schmidt, Xavier Niel and Yuri Milner”
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About H:
H exists to push the boundaries of superintelligence with agentic AI. By automating complex, multi-step tasks typically performed by humans, AI agents will help unlock full human potential.
H is hiring the world’s best AI talent, seeking those who are dedicated as much to building safely and responsibly as to advancing disruptive agentic capabilities. We promote a mindset of openness, learning, and collaboration, where everyone has something to contribute.
About the Team: The AI Data team advances the performance of Large Language Models (LLMs) and Vision-Language Models (VLMs) through cutting-edge data-centric techniques. From synthetic data generation to model distillation and AI-driven preference alignment, we develop high-quality datasets that enhance model efficiency, reasoning, and adaptability. Our work directly impacts the training and fine-tuning of frontier AI systems, ensuring they learn from richer, more diverse, and better-structured data.
Join us in shaping the future of AI through cutting-edge data optimization. We’re looking for driven individuals who thrive in fast-changing environments, adapt to new research paradigms, and eagerly take on challenges—whether deploying models, inspecting data, or pioneering new synthetic and reinforcement learning data methods.
Key Responsibilities:
Develop and implement cutting-edge data strategies to improve the performance, efficiency, and applicability of LLMs, VLMs and Action Models:
Requirements:
Location:
What We Offer:
If you want to change the status quo in AI, join us.
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Technical skills:
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Soft skills:
Nice to Have: