Senior Applied Scientist, Delivery Foundation Model

Amazon Amazon · Big Tech · Santa Clara, CA · Applied Science

Senior Applied Scientist role focused on developing and implementing novel deep learning foundation models, combining multiple modalities (image, video, geospatial) for logistics use cases. The role involves training models at scale, optimizing for inference, collaborating with other teams, guiding technical direction, and mentoring junior scientists. It spans the full spectrum from data preparation to model training, evaluation, and inference.

What you'd actually do

  1. Design and implement novel deep learning architectures combining a multitude of modalities, including image, video, and geospatial data.
  2. 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.
  3. 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.
  4. Guide technical direction for specific research initiatives, ensuring robust performance in production environments.
  5. Mentor fellow scientists while maintaining strong individual technical contributions.

Skills

Required

  • PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 10+ years of industry or academic research experience
  • 5+ years of building machine learning models or developing algorithms for business application experience
  • 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
  • Experience mentoring junior scientists / engineers

Nice to have

  • Experience building foundation models for industry or research
  • Experience designing multi-modal model architectures
  • Experience building models for motion prediction, e.g. autonomous driving
  • Track record of successful production ML deployments
  • Experience with large-scale distributed environments for ML training and inference
  • History of impactful first-author publications at major conferences

What the JD emphasized

  • foundation models
  • multimodal
  • production environments
  • large-scale distributed environments for ML training and inference

Other signals

  • foundation models
  • multimodal
  • large-scale training
  • production deployment