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Description

AWS AI Research and Engineering (AIRE) is looking for world class scientists and engineers to work on the development of autonomous AI agents. 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 learning techniques. 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 seamlessly combine them, and how to scale the modeling methods to learn with huge models and on large datasets. We seek a strong technical leader with domain expertise in machine learning, large language models and multimodal models, reinforcement learning and setting up simulation environments to benchmark and evaluate.

AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services.

A day in the life

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Hybrid Work

We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

About the team

We are open to hiring candidates to work out of one of the following locations:

Santa Clara, CA, USA

Basic Qualifications

• PhD in Computer Science, Electrical Engineering or similar with 3+ years of industrial AI research experience or Master's degree in Computer Science (and similar) with 7+ years of industrial AI research experience

• Experience in machine learning, deep learning, reinforcement learning, computer vision, robotics, or NLP.

• Strong publications record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent.

• Experienced programmer in Python, Java, or C++, and deep learning framework such as Pytorch, tensorflow, JAX, etc.

• Outstanding engineering skills for rapid research prototyping.

Preferred Qualifications

• 3+ years experience in building machine learning models for business applications.

• Hands-on experience in training or fine-tuning large (language or multimodal) generative models.

• Familiarity with distributed training, inference, acceleration method/implementation/library for LLMs or large-scale ML in general.

• Familiarity with ViT, diffusion models, RLHF, LLM agents, instruction finetuning and user alignment is a plus.

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 $136,000/year in our lowest geographic market up to $260,000/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. This position will remain posted until filled. Applicants should apply via our internal or external career site.