Description

　　AWS AI/ML is looking for world class scientists and engineers to work on foundation models, large-scale representation learning, and distributed learning methods and systems. 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

　　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. Amazon’s 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 isn’t about how many hours you spend at home or at work; it’s 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 we’re 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

　　10+ years of relevant, broad research experience after PhD degree or equivalent.

　　Deep expertise in foundational models as well as knowledge of the latest trends in related areas in Machine Learning.

　　Proficiency in programming for algorithm and code reviews.

　　Strong core competency in building solutions

　　Track record of successful projects in algorithm design and product development.

　　Publications at top-tier peer-reviewed conferences or journals.

　　Strong prior experience with mentorship and/or management of senior scientists and engineers.

　　Preferred Qualifications

　　PhD in Computer Science, Machine Learning, Mathematics, or related quantitative discipline.

　　Expert level skills across many Machine Learning methodologies.

　　Published peer reviewed papers and journals at top rated academic venues.

　　Experience delivering complex end-to-end global ML solutions that run at very big scale.

　　Experience with access management and security solutions.

　　Effective verbal and written communication skills with non-technical and technical audiences.

　　Experience working with real-world data sets and building scalable models from big data.

　　Experience thinking strategically and with tactical execution.

　　Experience recruiting high caliber talent.

　　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.

　　Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $159,100/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.