About Us

We are a well-funded, early-stage AI lab focused on building the next generation of frontier multimodal AI models. Founded by former DeepMind researchers, including Andrew Dai, who was previously a leader on Gemini. Our team currently consists of 20 world-class scientists and engineers. We raised $55M in seed funding from Striker Ventures, Menlo Ventures, Altimeter Capital, and NVIDIA. We are tackling some of the hardest problems in artificial intelligence, and we are growing fast.

About the Role

As a foundation model company, Elorian aims to empower robotics developers through advanced visual reasoning, spatial understanding, and high-quality robotics data solutions. We are looking for researchers and engineers with a background in robotics who want to apply their domain expertise to foundation-scale AI. Instead of focusing solely on isolated robot hardware or narrow policies, you will collaborate closely with our core foundation model research team to infuse physical-world priors into our models, address real-world robotics challenges, and develop foundational capabilities that generalize across a broad spectrum of robotics applications.

What You Will Do

• Develop Visual & Spatial Intelligence for Robotics: Advance and evaluate visual reasoning, 3D spatial understanding, and physical affordance capabilities directly within our multimodal foundation models to support downstream robotic perception and control.

• Architect Robotics Data Pipelines: Design scalable data pipelines—including data collection, teleoperation and trajectory annotation, automated quality assessment, and evaluation frameworks for multi-modal robotic data.

• Explore Foundation-Driven Embodied Reasoning: Investigate and implement novel approaches to robotic task planning, hierarchical reasoning, and decision-making powered by multimodal foundation models and Vision-Language-Action (VLA) architectures.

• Bridge Foundation Models & Robotics Applications: Collaborate closely with core foundation model researchers and robotics partners to identify real-world bottlenecks, evaluate model capabilities, and build impactful foundational AI solutions for the robotics ecosystem.

What We Are Looking For

• Strong background in robotics (research or engineering), with first-hand experience in robotic perception, planning, control, or robot learning.

• Genuine excitement to transition robotics domain knowledge into large-scale deep learning, multimodal architectures, and foundation model research.

• Solid experience with machine learning and hands-on familiarity with modern LLMs, multimodal foundation models (VLMs), or transformer architectures.

• Strong research and problem-solving skills, with the ability to independently investigate open-ended, complex technical challenges.

Nice to Have

• Experience with robotics simulation environments (e.g., Isaac Sim, MuJoCo) for large-scale data generation, policy evaluation, or model pre-training.

• Experience with robotics datasets, trajectory annotation, task decomposition, and benchmark evaluation for physical systems.

• Experience applying, fine-tuning, or developing LLMs, VLMs, or Vision-Language-Action (VLA) models for robotics problems.

• Background working with real-world robotic systems (manipulation, navigation, or autonomous agents) and understanding the practical limits of deploying policies to physical hardware.

• Deep expertise in robotic planning, 3D spatial reasoning, affordance modeling, or embodied intelligence.