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Description

AWS Applications and Higher Level Abstractions (Apps) provides horizontal and industry vertical applications for business users with the same on-demand scalability, reliability, pay-as-you-go pricing, and machine learning expertise that drive AWS services. The AWS Applications group includes services such as Amazon Connect (a cost-effective cloud contact center), our End User Computing (including Amazon Workspaces, AppStream, etc.), Marketing Tech (Amazon Pinpoint), and Autonomous Checkout and Biometric Identity Services (Just Walk Out, Amazon One) for retail, sports, travel, and other verticals.

Amazon Web Services (AWS) offers a broad set of global compute, storage, database, analytics, application, and deployment services that help organizations move faster, lower IT costs, and scale applications. These services are trusted by the largest enterprises and the hottest start-ups to power a wide variety of workloads including web and mobile applications, data processing and warehousing, storage, archive, and many others.

AWS Applications is building services in Supply Chain Management and is looking for a Machine Learning Engineer (MLE) to work on next generation supply chain systems including demand planning, supply planning and sustainability which will be used by our customers across a wide range of industries.

We operate a fast growing business and our journey has only started. Our mission is to build the most efficient and optimal supply chain software on the planet, using our science and technology as our biggest advantage. We aim to leverage cutting edge technologies in optimization, operations research, and machine learning to grow our businesses.

As an MLE, you will help design, implement and deploy state-of-the-art models and solutions used by users worldwide. As part of your role you will regularly interact with applied scientists, data scientists, software engineering teams and business leadership. The focus of this role is to develop, and deploy models to improve state-of-the-art for time series. Our team is also working on an assistant solution allowing our users to ask data questions in natural language and get intelligent insights and exceptions.

Key job responsibilities

• Help define and partner with external teams on data strategy for training foundational models.

• Help support scientists on tooling including notebooks and training pipelines.

• Establish MLOps best practices and operations for the team.

About the team

ABOUT AWS:

Diverse Experiences

Amazon values diverse experiences. Even if you do not meet all of the preferred 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.

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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

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 and 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.

Basic Qualifications

• 3+ years of non-internship professional software development experience

• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience

• Experience programming with at least one software programming language

• 2+ years of industrial experience with Machine learning systems and big data processing

• Experience working with cross-functional teams including communicating with other technical teams, product management, and senior management

Preferred Qualifications

• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

• Bachelor's degree in computer science or equivalent

• Coursework in machine learning

• 2+ years of industrial experience with AWS Experience with building or customizing large language models.

• Java and Python experience

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 $129,300/year in our lowest geographic market up to $223,600/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.