We are seeking an exceptional Senior 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

BASIC QUALIFICATIONS

- 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.

PREFERRED QUALIFICATIONS

- 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

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, CA, SANTA CLARA - 192,200.00 - 260,000.00 USD annually