DESCRIPTION
AWS AI/ML is looking for a talented Postdoctoral Scientist to join its AI Research and Education group working on foundation models, large-scale representation learning, and distributed learning methods and systems for a one-year, full-time research position. At AWS AI/ML you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and innovate on new representation learning solutions. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists.
Large-scale foundation models have been the powerhouse in many of the recent advancements in computer vision, natural language processing, automatic speech recognition, recommendation systems, and time series modeling. Developing such models requires not only skillful modeling in individual modalities, but also understanding of how to synergistically combine them, and how to scale the modeling methods to learn with huge models and on large datasets. Join us to work as an integral part of a team that has diverse experiences in this space. We actively work on these areas:
* Hardware-informed efficient model architecture, training objective and curriculum design
* Distributed training, accelerated optimization methods
* Continual learning, multi-task/meta learning
* Reasoning, interactive learning, reinforcement learning
* Robustness, privacy, model watermarking
* Model compression, distillation, pruning, sparsification, quantization
In this role, you will have the opportunity to:
- Leverage advanced statistical techniques and machine learning models to extract valuable insights from historical data and comparable item information.
- Tackle data scarcity challenges by developing innovative approaches to maximize the utility of available data sources.
- Collaborate with cross-functional teams to develop and deploy production-ready solutions.
- Participate in research activities, including publishing papers, attending conferences, and collaborating with academic institutions to advance the state-of-the-art in relevant fields.
Key job responsibilities
In this role you will:
Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazons vibrant and diverse global science community.
Publish your innovation in top-tier academic venues and hone your presentation skills.
Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.
A day in the life
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazons culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Work/Life Balance
Our team puts a high value on work-life balance. It isnt about how many hours you spend at home or at work; its about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and were building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
We are open to hiring candidates to work out of one of the following locations:
Santa Clara, CA, USA
BASIC QUALIFICATIONS
Basic qualifications include:
- PhD in a relevant field, received within 2 years of starting the program
- Proven publication record in Machine Learning, Computer Science, Computer Engineering, or other related technical fields
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
-Experience programming in Java, C++, Python or related language
PREFERRED QUALIFICATIONS
Postdocs demonstrate the following preferred job qualifications:
- Ability to independently deliver results in a fast-paced environment
- Publications at top-tier, peer-reviewed conferences and/or journals
- Exceptional verbal and written communication skills
- Expert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategies
Required application materials:
- CV, which lists all peer-reviewed publications and conferences,
- Research statement that outlines your research achievements and future research interests, and
- A journal article or book chapter that demonstrates your domain expertise.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
