Robotic AI Engineer/Applied Scientist - Foundation Models

About this role

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:

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

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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.

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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.

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

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

Qualifications

Must-have:

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

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

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

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

Nice-to-have:

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

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Experience with large-scale distributed training and model compression.

• Experience with deployment of models to edge devices (NVIDIA Jetson/Orin) for real-time inference.

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