Job Description
DESCRIPTION
Amazon Robotics is seeking an exceptional Applied Scientist to join our Foundation Models team. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models.
At Amazon Robotics, we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence.
We are pioneering the development of robotics foundation models that:
- Enable unprecedented generalization across diverse tasks
- Integrate multi-modal learning capabilities (visual, tactile, linguistic)
- Accelerate skill acquisition through demonstration learning
- Enhance robotic perception and environmental understanding
- Streamline development processes through reusable capabilities
The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment.
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 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.
- Experimentation and Validation: Design and execute experiments to test model capabilities on the simulator and on the embodiment, validate performance across different scenarios, create a baseline and iteratively improve model performance.
- 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
- Research: Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions.
- Collaboration: Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies.
A day in the life
Amazon offers a full range of benefits for you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan
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!
BASIC QUALIFICATIONS
- 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
Job Tags
Full time, Temporary work, Seasonal work, Worldwide,