Software Development Engineer, AWS SageMaker

DESCRIPTION

Job summary
Interested in machine learning, and empowering the world to do more and better machine learning? Amazon SageMaker , Amazon Web Service’s (AWS) fully managed Machine Learning (ML) platform team is building customer-facing services to catalyze data scientists and developers in their machine learning endeavors. SageMaker takes away the heavy-lifting normally associated with large-scale Machine Learning implementations, so that developers and scientists can focus on solving the business problem at hand.

While ML is no longer a new concept, applying ML in production to solve real-world problems at scale is still in this infancy. Today, over 70% AI/ML projects don’t see the light of day due to the challenges in productionizing the model. Our mission is to build a collection of services and tools to help customer in making their ML projects successful. We solve challenges in the new area of “MLOps” that will transform ML just like how DevOps transformed software development over the past decades. You will design, implement, test, operate, and support cross-cutting services for new products. Your work will enable customers to build and automate their end-to-end ML workflows that are fully-managed, highly scalable, available, configurable, accessible, and easy-to-use. Your work may span across the backend distributed systems, open-source libraries, and the interactive UI in SageMaker Studio (for frontend/full-stack positions).

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!

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.

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.

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.

BASIC QUALIFICATIONS

• 1+ years of experience contributing to the system design or architecture (architecture, design patterns, reliability and scaling) of new and current systems.
• 2+ years of non-internship professional software development experience
• Programming experience with at least one software programming language.

• Bachelor’s degree in Computer Science, Computer Engineering or related field
• Solid Computer Science fundamentals: data structures, object-oriented design, algorithm, problem solving, and complexity analysis

PREFERRED QUALIFICATIONS

• Experience building software systems that have been successfully delivered to customers
• 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 defining system architectures and exploring technical tradeoffs
• Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
• Hands-on expertise in building and operating complex distributed systems
• Master’s degree in Computer Science or related field
• Experience building and operating mission critical, highly available (24×7) systems
• Experience with machine learning, data mining, and/or deep learning 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.