Senior Applied Scientist, Delivery Foundation Model
Jobverse.io · Santa Clara, UT · 1 wk ago
ManufacturingFull-time
About the role
Amazon is seeking a Senior Applied Scientist to join its Delivery Foundation Model team and advance logistics through artificial intelligence and foundation models. The role focuses on developing multimodal deep learning architectures, training and deploying models at Amazon scale, guiding research initiatives, collaborating across science and engineering teams, and mentoring fellow scientists.
Responsibilities
- Design and implement novel deep learning architectures combining a multitude of modalities, including image, video, and geospatial data
- Solve computational problems to train foundation models on vast amounts of Amazon data and infer at Amazon scale, taking advantage of latest developments in hardware and deep learning libraries
- As a foundation model developer, collaborate with multiple science and engineering teams to help build adaptations that power use cases across Amazon Last Mile deliveries, improving experience and safety of a delivery driver, an Amazon customer, and improving efficiency of Amazon delivery network
- Guide technical direction for specific research initiatives, ensuring robust performance in production environments
- Mentor fellow scientists while maintaining strong individual technical contributions
- Develop and implement novel foundation model architectures, working hands-on with data and our extensive training and evaluation infrastructure
- Guide and support fellow scientists in solving complex technical challenges, from trajectory planning to efficient multi-task learning
- Guide and support fellow engineers in building scalable and reusable infra to support model training, evaluation, and inference
- Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems
- Drive technical discussions within the team and key stakeholders
- Conduct experiments and prototype new ideas
- Mentor team members while maintaining significant hands-on contribution to technical solutions