Job Description
DESCRIPTION
Join the next science and engineering revolution at Amazon's Delivery Foundation Model team, where you'll work alongside world-class scientists and engineers to pioneer the next frontier of logistics through advanced AI and foundation models.
We are seeking an exceptional Principal Applied Scientist to help develop innovative foundation models that enable delivery of billions of packages worldwide. In this role, you'll combine highly technical work with scientific leadership, ensuring the team delivers robust solutions for dynamic real-world environments. Your team will leverage Amazon's vast data and computational resources to tackle ambitious problems across a diverse set of Amazon delivery use cases.
Key job 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.
A day in the life
As a member of the Delivery Foundation Model team, you’ll spend your day on the following:
- 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 and key stakeholders
- Conduct experiments and prototype new ideas
- Mentor team members while maintaining significant hands-on contribution to technical solutions
About the team
The Delivery Foundation Model team combines ambitious research vision with real-world impact. Our foundation models provide generative reasoning capabilities required to meet the demands of Amazon's global Last Mile delivery network. We leverage Amazon's unparalleled computational infrastructure and extensive datasets to deploy state-of-the-art foundation models to improve the safety, quality, and efficiency of Amazon deliveries. Our work spans the full spectrum of foundation model development, from multimodal training using images, videos, and sensor data, to sophisticated modeling strategies that can handle diverse real-world scenarios. We build everything end to end, from data preparation to model training and evaluation to inference, along with all the tooling needed to understand and analyze model performance.
Join us if you're excited about pushing the boundaries of what's possible in logistics, working with world-class scientists and engineers, and seeing your innovations deployed at unprecedented scale.
BASIC QUALIFICATIONS
- PhD or Master's degree and 8+ years of applied machine learning experience.
- Experience designing novel deep learning model architectures, building models from scratch
- Proficient with Data, experience with SQL and Spark
- Expert coders comfortable working in production environments using Python, C++ or other languages
- Strong publication record at top-tier conferences (NeurIPS, ICML, ICLR, CVPR, ICCV, RSS, CoRL) OR Demonstrated experience in applying machine learning innovation in industry
- Extensive track record of leading technical projects
- Experience mentoring junior scientists / engineers.
Job Tags
Full time, Worldwide,