Applied Scientist, Amazon Robotics

• We are pioneering the development of robotics foundation models that:
• Enable unprecedented generalization across diverse tasks
• Integrate multi-modal learning capabilities (visual, depth, force, tactile, linguistic)
• Accelerate policy skill acquisition through imitation learning and reinforcement learning
• Enhance robotic perception and environmental understanding
• Streamline development processes through reusable capabilities
• Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration.
• Key job responsibilities
• As an Applied Scientist in the Applied AI and Robotics Foundations Model team, you will:
• Model Development and Training: Designing and implementing the model architectures, training and fine tuning the foundation models using various datasets, and optimize the model performance through iterative experiments
• Data Management: Process and prepare training data, including data governance, provenance tracking, data quality checks and creating reusable data pipelines.
• Code Development: Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs
• A day in the life
• The benefits that generally apply to regular, full-time employees include:
• If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
• At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
• About the team
• PhD, or Master's degree and 4+ years of building machine learning models or developing algorithms for business application experience
• 2+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience
• Experience in patents or publications at top-tier peer-reviewed conferences or journals
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
• Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
• Experience applying theoretical models in an applied environment

None flagged.