Machine Learning Engineer, AWS Supply Chain
Job ID: 2703671 | Amazon Web Services, Inc.
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.
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.
