Job description

About Maven Maven Robotics designs, builds, and deploys intelligent robotics for logistics and manufacturing. Maven is building the first general-purpose robotics system for industrial work. Our mission is to activate autonomous labor at scale and build toward infinitely elastic industrial capacity. We’re a team of engineers, researchers, and operators who have spent our careers working on the hardest problems in AI, robotics, engineering, and autonomous systems. We work at the intersection of advanced research and real-world engineering, turning ideas into prototypes and deployed systems. At Maven, we build around the realities of industrial work. The robots are designed from first principles for complex physical environments and rigorous commercial standards. They master real tasks that deliver immediate impact, industrial-grade reliability, and intelligence that compounds at scale. We’re growing an ambitious team of people who think in systems, move quickly, and are builders at heart. About the Role 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. 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). What You’ll Do 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 What We’re Looking For 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) Equal Opportunity Maven Robotics is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Requirements

Must-haves

What You’ll Do
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
What We’re Looking For
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-haves

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)

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningpython

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Vision