Interested in Machine Learning? Amazon SageMaker is a fully managed Machine Learning platform that makes it easy to build ML models, manage them, and integrate them with custom applications for online predictions. Amazon SageMaker (https://aws.amazon.com/sagemaker/) takes away the heavy-lifting normally associated with large-scale Machine Learning implementations, so that developers and scientists can focus on the truly creative work of modeling and solving the business problem at hand.
You will work in a diverse team to build out the foundational technology for SageMaker's managed data processing service. You will design, implement, test, operate, and support cross-cutting services for this product.
We are looking for a software engineer who is excited about our mission. You'll assist in gathering and analyzing business and functional requirements, and translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture. You will serve as a key technical resource in the full development cycle, from conception to delivery and maintenance. You will produce comprehensive, usable software documentation; recommend changes in development, maintenance and system standards. You will own delivery of entire piece of the system and serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers. You will do everything from determining priorities and designing features to re-architecture as necessary, automated testing and mentoring others. The best candidates show true end-to-end ownership.
At SageMaker, there are immense learning as well as growth opportunities. This is a great team to come to have a huge impact on AWS and the world's customers we serve!
• SageMaker is one of the fastest growing AWS services. You will join the founding team in innovating and building the next generation of features in the SageMaker Processing service. It represents a unique opportunity to contribute to the data processing backbone of Amazon's ML platform.
• Applying ML in real-life is still in its early stage and ML practitioners face similar challenges as software engineering teams faced a decade ago. Our mission is to solve challenges in ML like what DevOps solved for software development over the past 10 years. This is a new area in ML with lots of evolvement in concepts, methodology, and solutions.
• We have a deep mix of senior talent presenting itself in Principals and Distinguished Engineers that lead to an extensive level of learning and coaching. This is a great opportunity if you are looking to get into the AI/ML space and want to get hands-on experience building ML platform services at scale.
• Our services are built on native AWS. We embrace modern technologies and server-less/micro-service based architectures, which maximize engineering efficiency and operational excellence.
• A place to exercise your Customer Obsession and Think Big muscles SDEs play a big role in shaping the product and defining customer experience.
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.
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
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.
• 2+ years of non-internship professional software development experience
• Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
• 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
• Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
• Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
• Experience building and operating mission critical, highly available (24x7) systems
• Experience with machine learning and/or distributed data processing frameworks 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.
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 we 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.