RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability.
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Design and deploy vision-language(-action) models (VLM/VLA) for contextual understanding and generalized robot action policies.
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Develop and train world models for action-conditioned prediction, long-horizon planning, and environment simulation — enabling robots to reason about the consequences of their actions before execution.
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Research approaches to improve world model fidelity using multi-modal inputs including vision, language, proprioception, and spatial representations.
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Develop foundation models with spatial reasoning capabilities to achieve high-precision robotic actions.
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Integrate multi-modal data sources (vision, language, speech, etc.) to enable natural human-robot communication.
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Optimize and deploy models as production-grade solutions on RoboForce robotic platforms.
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PhD degree in Machine Learning, Robotics, or related field, or Master's degree with 4+ years of relevant experience.
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Proficiency in Python and deep learning frameworks (e.g., PyTorch, JAX).
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Expertise in large foundation models (VLM, VLA, etc.).
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Strong understanding of world model architectures and action-conditioned generative modeling for robot learning.
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Decent understanding of multimodal models, modern ML architectures (transformers, diffusion models, etc.).
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Requires 5 days/week in-office collaboration with the teams.
Compensation: Salary $200,000–$360,000 USD + Bonus + Equity
The base salary range above represents the expected compensation for this full-time U.S. position. Final compensation will be determined based on role scope, level, location, job-related skills, experience, and relevant education or training, and may fall outside the listed range in exceptional cases.
