Robotic AI Engineer/Applied Scientist - Foundation Models

Maven Robotics

  • San Francisco, California
  • 30+ days ago
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    Skills

    • Algorithmsunmatched
    • Architectural Designunmatched
    • Architectural Servicesunmatched
    • Artificial Intelligence (AI)unmatched
    • Automationunmatched
    • Data Collectionunmatched
    • Data Modelingunmatched
    • Internet Videounmatched
    • JAX (Java API for XML)unmatched
    • Machine Learningunmatched
    • Mavenunmatched
    • Motor Control Systemsunmatched
    • Product Demonstrationunmatched
    • Python Programming/Scripting Languageunmatched
    • Reinforcement Learningunmatched
    • Roboticsunmatched

    Description

    Company Overview

    Maven Robotics is building the world’s leading general-purpose robots and providing physical AI solutions for the most challenging industrial autonomy tasks.

    Operating in stealth, we are assembling a team of world-class innovators who think from first principles. Our mission is to achieve human-level task success rates in complex environments, even when faced with limited fine-tuning data or evolving robotic hardware. We value unwavering truth-seeking, humility, and relentless determination.

    Role Description

    We are seeking exceptional AI researchers and engineers to architect the neural backbone of our general-purpose robots. You will design the Vision-Language-Action (VLA) frameworks or Action World Models that allow our robots to reason, adapt, and succeed where traditional automation fails.

    Note on Leveling: We are hiring across all levels (from early-career to staff/principal). You are not expected to be a master of every domain listed below; however, you must be able to justify world-class excellence in at least one core factor (e.g., model architecture, RL formulations, or high-scale data systems).

    In this role, you will:

    • Architect Embodied Foundations: Design model architectures (VLA, World Models, etc.) that achieve ultra-high task success rates with minimal human demonstrations.

    • Master Data Efficiency: Develop novel co-training strategies and efficient learning algorithms that leverage diverse data sources—from Internet-scale video to sparse, high-fidelity human interventions.

    • Generalize Cross Embodiments: Build models capable of zero-shot or few-shot adaptation to new robot configurations, maintaining a high success rate even when proprietary hardware and actuation systems evolve.

    • Innovate Real-World RL: Formulate and deploy novel Reinforcement Learning and policy extraction methods specifically designed for physical, real-world manipulation.

    • Design the Data Loop: Collaborate on advanced data collection systems to capture critical human intervention data for model bootstrapping.

    Qualifications

    Must-have:

    • MS or PhD in CS, Robotics, Machine Learning, or a related field (or equivalent industry experience).

    • Deep Technical Mastery: Advanced understanding of transformers, multi-modal alignment, and mapping perception to high-frequency motor control.

    • Specialized Excellence: Proven ability to innovate—not just implement—within one or more areas: VLA models, Real-world RL, or large-scale Data Infrastructure.

    • Software Excellence: Expert-level Python and deep familiarity with PyTorch or JAX

    Nice-to-have:

    • A track record of high-impact publications (NeurIPS, ICRA, RSS, CVPR) or significant open-source contributions.

    • Experience with large-scale distributed training and model compression.

    • Experience with deployment of models to edge devices (NVIDIA Jetson/Orin) for real-time inference.
    • General knowledge of robotics principles (kinematics, dynamics).

    Why Maven Robotics?

    You will be working on a unique in-house robot platform that is evolving alongside your models. We don't just want to reach 90% success; we are building the architectural breakthroughs required to reach 99.9% in the real world.

    Numbers & Facts

    LocationSan Francisco, California
    Websitehttps://www.mavenrobotics.ai

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