Data Infrastructure at Genesis (London, United Kingdom)

Genesis· London, United Kingdom·1d ago

Role details

Work type

Hybrid

Employment

Full-Time

Job description

Design, build, and maintain large-scale data pipelines (batch and streaming) for robotics foundation model training and evaluation at petabyte scale
Own core data infrastructure: data model, storage systems, ingestion pipelines, transformation frameworks, and orchestration layers
Standardize data models and unify processing pipelines across real-world teleoperation and synthetic simulation datasets
Collaborate with a team of driven individuals committed to building general-purpose Physical AI

Excellent software engineering skills (Python, Go, or similar)
Extensive experience designing, building, and maintaining large-scale data pipelines (8+ years)
Deep understanding of distributed systems (Spark, Kafka, or similar)
Extensive experience with data storage technologies (data lakes, warehouses, object stores like S3)
Experience running and maintaining production-grade infrastructure (Kubernetes, Terraform)
Bonus: Experience supporting AI systems, in particular embodied AI like self-driving

Culture: Values include candor, responsibility, limitless ambition, and a joyful journey. The team is described as multicultural, optimistic, and pragmatic.
Work model: Hybrid/office-based presence in Paris, San Francisco Bay Area, and London. No explicit remote policy mentioned, but the company emphasizes in-person collaboration.
Engineering culture: Builders get to work on the hardest problems in robotics and AI – from foundation models to hardware design to data systems. The team includes pioneers of generative simulation, Diffusion Policy, and GPU compilers.
Notable perks: The chance to shape a category-defining general-purpose robot; close collaboration with world-class investors and advisors; fast-growing startup with significant resources ($105M seed).

One-liner: Genesis AI is a full-stack robotics company building general-purpose robots with human-level dexterity and intelligence, powered by its own foundation model and hardware.
Entity Type: Private (Seed stage – $105M raised)
Headquarters: Paris, France (with offices in the San Francisco Bay Area and London)
Founded: 2024 (emerged from stealth in July 2025)
Founders: Zhou Xian (CEO), Théophile Gervet (President & Co-founder), Yi-Ling Qiao (Co-founder), Tsun-Hsuan Wang (Co-founder)

Primary industry: Robotics Engineering / General-Purpose Robotics
Target customers: Enterprises in manufacturing, laboratories, hospitals, and logistics; future expansion into homes.
Mission: “Build the world’s most capable robots that unlock new possibilities for humans.”

Eno (General-Purpose Robot): A full-body robot designed to operate reliably in factories, labs, hospitals, and homes. Driven by the GENE foundation model, it features 20 active, back-drivable degrees of freedom in its hands – matching human size and dexterity.
GENE-26.5 (Foundation Model): The AI model that powers Eno. It understands goals, reasons through changing conditions, and completes tasks end-to-end. Trained on massive human-based internet video data and proprietary simulation.
Data Collection Glove: A lightweight, sensor-loaded glove worn by humans to collect high-quality manipulation data in real-world settings (e.g., lab technicians, manufacturing workers). This glove bridges the “embodiment gap” and feeds the model with human skill data.
Simulation System: A proprietary simulation environment that accelerates model training and evaluation, reducing the iteration bottleneck.

Valuation: Not disclosed
Key Metric: Total funding of $105M (Seed round, July 2025)
Notable Investors/Partners: Eclipse (co-lead), Khosla Ventures (co-lead), Bpifrance, HSG; individual investors Eric Schmidt, Xavier Niel, Daniela Rus, Vladlen Koltun. Hardware manufacturing partner: Wuji Tech (China).
Growth Signals:
- Headcount grew from stealth to ~53–60 employees across Paris, Bay Area, and London (monthly growth +16% on LinkedIn).
- 29 active job postings as of mid-2026, with a +262.5% monthly increase in openings.
- Demonstrated a wide range of manipulation tasks (cooking, piano, Rubik’s cube, lab work) in public demos.
- In talks with multiple customers for commercial deployment in pharma and manufacturing.

Full-stack integration: Genesis controls both the AI model and the robotic hardware, enabling tighter optimization and faster iteration than companies that only do software or hardware.
Human-like dexterity: The robotic hand matches human size, shape, and 20 degrees of freedom, allowing direct transfer of human demonstration data without an “embodiment gap.”
Data flywheel: The combination of a low-friction data collection glove, simulation, and egocentric video creates a scalable pipeline for building a “human skill library.”
World-class team: Founders and early engineers have backgrounds from Mistral AI, NVIDIA, Google DeepMind, Apple Intelligence, Unity, Epic, and leading robotics labs (Berkeley, CMU).

Go full stack: Continue integrating model, hardware, and data collection to deliver a complete general-purpose robot.
Commercial rollout: Target early customers in pharmaceutical labs, manufacturing, and other industrial settings where dexterous manipulation is critical.
Scale data collection: Expand the use of the data glove (both internally and with third-party partners) to rapidly grow the model’s skill repertoire.
Global hiring: Aggressively grow the team across Paris, Bay Area, and London, especially in ML, simulation, rendering, and robotics engineering.

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