Job Details

We are looking for people who have demonstrated incredible findings from top universities or shipped product at top 1% organizations e.g. Tesla, Boston Dynamics etc.

We are seeking a Senior/Principal Research Engineer to lead the development and deployment of next-generation multi-modal AI systems for our robot platform. This role requires a unique blend of deep theoretical knowledge (applied mathematics, computer vision) and hands-on experience shipping large-scale, mission-critical products.

The ideal candidate will translate their expertise in multi-modal foundation models (LLMs/VLMs) into the real-time, physical autonomy required by a robot, driving innovation from architectural concept through deployment.

Key Responsibilities and Impact

• Robot Vision Architecture: Define and scope the complete vision architecture for our humanoid robot, including sensor selection, onboard compute specifications, and the design of multi-modal algorithms that enable robust autonomy.
• Foundation Model Adaptation for Embodiment: Lead the fine-tuning, adaptation, and distillation of LLMs/VLMs for domain-specific, real-time applications, enabling the robot to perform complex, language-guided tasks (RAG workflows) in physical space.
• 3D Perception & Spatial Awareness: Architect and implement algorithms for multi-view 3D reconstruction, Structure from Motion (SfM), and SLAM to provide the humanoid with accurate spatial understanding and the ability to navigate and interact with its environment.
• Real-Time Human-Robot Interaction (HRI): Develop and deploy robust, real-time, multi-modal algorithms to analyze and understand complex human activity, intent, and behavior, allowing the robot to collaborate naturally.
• Full-Stack Deployment: Lead a distributed team in implementing algorithms in Python and C/C++, deploying them as scalable services using Docker, AWS/GCP, and CI/CD pipelines for both simulation and physical robot deployment.
• Research & Strategy: Drive strategic direction by selecting and evaluating cutting-edge technologies, and drafting patents for core intellectual property that defines the robot's intelligence.

Required Technical Qualifications

• Machine Learning & Vision for Robotics: Ph.D. in Electrical Engineering, Computer Science, or a related field with 10+ years of industry and research experience.
• Expertise in multi-modal representation learning architectures, including transformers, specifically applied to embodied systems.
• Deep practical experience with fine-tuning LLMs/VLMs, zero-shot learning, and RAG systems to facilitate natural language task execution.
• Expert-level knowledge of classical and modern computer vision techniques essential for robotics: 3D reconstruction, object detection, segmentation, and robust tracking.

Applied Mathematics & Control Systems

• Strong foundational knowledge in Statistics, Numerical PDEs, Variational Calculus, and Optimization methods.
• Experience applying advanced filtering and estimation techniques, such as Kalman Filter, Particle Filter, and adaptive control, to physical, real-time systems.

Software & Deployment

• Fluency in Python and C/C++ for high-performance algorithm implementation.
• Hands-on experience with industry-standard frameworks: PyTorch, OpenCV, VTK, and CMake.
• Proficiency with cloud services (AWS, Google Cloud) and DevOps tools (Docker, Jenkins) for scalable deployment of ML services and maintaining data pipelines.

Experience

• Proven track record in a leading role (e.g., Senior Research Engineer, CTO) at a top-tier technology company (Apple, Tesla, Figure etc.).
• Demonstrated ability to transition technology from research prototype to shippable, production-ready product within an autonomous system context.

Seniority level: Mid-Senior level

Employment type: Full-time

Job function: Information Technology, Design, and Other

Industries: Robotics Engineering, Robot Manufacturing, and Engineering Services