Senior AI Research Engineer (Embodied AI)
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Are you the one?
Imagine joining a team at the forefront of artificial intelligence research, where you’ll pioneer cutting-edge deep learning models that empower intelligent systems to perceive and interact with complex environments. We’re pushing the boundaries of multimodal AI, integrating diverse data sources to enable robust decision-making and adaptive behavior in advanced robotic systems. If you’re driven by the challenge of developing transformative AI that bridges perception, cognition, and action, we want to hear from you.
Responsibilities:
• Conduct research and develop advanced deep learning models—including transformer architectures and convolutional networks—for robust multimodal data integration.
• Innovate algorithms that extract and fuse representations from heterogeneous inputs (e.g., visual, auditory, proprioceptive signals) to support autonomous decision-making.
• Explore self-supervised, semi-supervised, and reinforcement learning techniques to enhance model generalization and performance.
• Collaborate with cross-functional teams, integrating AI solutions with simulation environments and hardware systems to validate model efficacy.
• Optimize and deploy scalable AI models on both edge devices and cloud platforms, ensuring high performance under real-world constraints.
Skills:
• Advanced expertise with deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• Strong research background in transformer-based models, multimodal fusion, and self-supervised learning methodologies.
• Experience in large-scale model training, hyperparameter tuning, and performance optimization for production environments.
• Proficiency in Python, with solid knowledge of C++ for integrating AI models within complex systems.
• Excellent analytical skills, with a proven track record of designing experiments, interpreting data, and driving innovative research.
Nice to have:
• Experience in integrating AI solutions with robotics platforms and real-time sensor data.
• Familiarity with distributed training frameworks and high-performance computing environments.
• Understanding of reinforcement learning strategies and simulation-based model validation.
• Contributions to peer-reviewed publications or open-source projects in advanced AI research.
About the job
Senior AI Research Engineer (Embodied AI)
To see similar active jobs please follow this link: Remote Development jobs
Are you the one?
Imagine joining a team at the forefront of artificial intelligence research, where you’ll pioneer cutting-edge deep learning models that empower intelligent systems to perceive and interact with complex environments. We’re pushing the boundaries of multimodal AI, integrating diverse data sources to enable robust decision-making and adaptive behavior in advanced robotic systems. If you’re driven by the challenge of developing transformative AI that bridges perception, cognition, and action, we want to hear from you.
Responsibilities:
• Conduct research and develop advanced deep learning models—including transformer architectures and convolutional networks—for robust multimodal data integration.
• Innovate algorithms that extract and fuse representations from heterogeneous inputs (e.g., visual, auditory, proprioceptive signals) to support autonomous decision-making.
• Explore self-supervised, semi-supervised, and reinforcement learning techniques to enhance model generalization and performance.
• Collaborate with cross-functional teams, integrating AI solutions with simulation environments and hardware systems to validate model efficacy.
• Optimize and deploy scalable AI models on both edge devices and cloud platforms, ensuring high performance under real-world constraints.
Skills:
• Advanced expertise with deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• Strong research background in transformer-based models, multimodal fusion, and self-supervised learning methodologies.
• Experience in large-scale model training, hyperparameter tuning, and performance optimization for production environments.
• Proficiency in Python, with solid knowledge of C++ for integrating AI models within complex systems.
• Excellent analytical skills, with a proven track record of designing experiments, interpreting data, and driving innovative research.
Nice to have:
• Experience in integrating AI solutions with robotics platforms and real-time sensor data.
• Familiarity with distributed training frameworks and high-performance computing environments.
• Understanding of reinforcement learning strategies and simulation-based model validation.
• Contributions to peer-reviewed publications or open-source projects in advanced AI research.