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Senior Software Engineer, AWS SageMaker Core Platform, Seattle, Washington

CategorySoftware Development
Job typeFull Time
CountryUnited States of America
In this role, you will build a new AWS service that is going to be trend setting in the machine learning and AI field. This is an area that requires solving the hardest engineering challenges to enable machine learning powered solutions for our customers. As a tier zero Amazon service our solutions have to be scalable, efficient, and fault tolerant. Experience with machine learning systems is preferred, but not required. You will deliver some of our most strategic technical projects, deliver large scalable systems, design new software systems at the cutting edge of distributed database technology and have a significant bottom-line impact on our business and competitive position. In addition to delivering critical software, you will draw from a deep and broad technical expertise to mentor engineers and provide leadership on complex technical issues. This position within the AWS AI team presents a unique and rare opportunity to get in on the ground floor within a fast growing business and help shape the technology, product and the business. A successful candidate will bring deep technical and software expertise, desire to have an industry wide impact and ability to work within a fast moving, startup environment in a large company to rapidly deliver services that have a broad business impact.

About Us
Inclusive Team Culture
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.

Work/Life Balance
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.

Mentorship & Career Growth

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.

Interested in making an impact on the Machine Learning and AI ecosystem? As an SDE on the Amazon SageMaker Studio Core Platform team, you'll own the core platform (control plane and data plane) for various interactive applications (e.g. JupyterLab). Our team's mission is to enable any interactive application to scale reliably and securely so any data scientist, developer, or student can launch a wholly configured and collaborative workspace in the cloud. You will work in the company of world experts and there are immense learning opportunities.

Engineers on this team get to:
• Develop in multiple layers of the stack including distributed workflows, high throughput data planes, linux networking, and system security.
• Build fundamental primitives in the cloud for enabling data scientists workflows.
• Develop/maintain operational rigor for a fast-growing AWS service.
Note that this is a backend engineering position.

Key Responsibilities:
• 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.
• Engage with customers and other AWS partners
• Serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers
• You'll be well supported with by a group with deep technical chops, including multiple senior and principal engineers.
What is SageMaker?
Amazon SageMaker (https://aws.amazon.com/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 batch or online predictions. 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.

What is SageMaker Studio?
SageMaker Studio is AWS' fully Integrated Development Environment for Machine Learning. It's our end-user-focused single-pane-of-glass for interfacing with SageMaker and a plethora of ML technologies. Read more at https://aws.amazon.com/blogs/aws/amazon-sagemaker-studio-the-first-fully-integrated-development-environment-for-machine-learning/

Basic Qualifications:
• 4+ years of professional software development experience
• 3+ years of programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
• 2+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
• Bachelor's Degree in Computer Science or related field or equivalent work experience
• Strong computer science fundamentals - data structures, algorithms design, complexity analysis, operating systems etc.
• Object-oriented design proficiency
• Strong analytical abilities and problem solving
• Strong inclination towards building high quality systems by testing mercilessly.
• Strong sense of ownership and willing to own end to end systems.
• Proficiency in, at least, one modern programming language such as Java, Go, Python, Scala, C++, C#.

Preferred Qualifications:
• Machine learning knowledge and experience.
• Experience building tools for data scientists and developers.
• Experience building complex software systems that have been successfully delivered to customers.
• Experience with highly distributed, multi-tenant systems with clear state-full/state-less boundaries.
• 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.
• Ability to take a project from scoping requirements through actual launch of the project.
• Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs.
• Deep hands-on technical expertise in: large scale systems engineering and/or full-stack development.

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.

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