APPLIED SCIENTIST, AWS DEEP LEARNING

Amazon
Santa Clara, CA, United States
$222.2K a year
Full-time
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Description

AWS AI / ML is looking for world class scientists and engineers to join its AI Research group working on building open-source automated ML solutions.

Our teams mission is to democratize machine learning by creating powerful open-source tools like AutoGluon for solving practical ML problems and revolutionize the rate and ease ML practitioners progress from problem formulation to deployed solution.

Our vision is to advance the state-of-the-art in automated ML to become the go-to tool for solving the vast majority of ML problems.

The team specializes in developing popular open-source software libraries like AutoGluon, GluonCV, GluonNLP. Building these solutions requires a solid foundation in machine learning infrastructure and deep learning technologies.

Key job responsibilities

We are seeking an experienced Applied Scientist for the team. This is a role that combines science knowledge (around machine learning, foundational models, AutoML), technical strength, and product focus.

It will be your job to develop novel ML systems and algorithms while working with the engineering team to integrate them into our open-source projects.

You will interact closely with the open-source, 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.

You will have the opportunity to publish in scientific conferences and journals, create white papers, write blogs, and have high visibility in the industry.

About the team

AWS Utility Computing (UC) provides product innovations from foundational services such as Amazons Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWSs services and features apart in the industry.

As a member of the UC organization, youll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.

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, hasnt followed a traditional path, or includes alternative experiences, dont let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats 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, its 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

Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll 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, theres nothing we cant 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.

Basic Qualifications

  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience building machine learning models or developing algorithms for business application
  • Experience in any of the following areas : algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred Qualifications

Published papers at ICML, NeurIPS, ICLR, AISTATS, AutoML, UAI, AAAI, IJCAI, KDD, CVPR, ICCV, ECCV, ACL, EMNLP, MLSys, OSDI, Eurosys, SC, or similar top-tier conferences and journals.

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 $222,200 / 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.

30+ days ago
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