Software Development Engineer, AWS SageMaker Studio

- 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
- 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

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.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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.
AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for customers who require specialized security solutions for their cloud services.

Amazon SageMaker Studio is the world’s first fully integrated development environment tailored for machine learning, and is growing rapidly to be the tool of choice for machine learning scientists and practitioners all around the world. All ML development activities including notebooks, experiment management, automatic model creation, debugging, and model and data drift detection can be performed within SageMaker Studio. While experimenting with different combination of inputs to fine tune models, users can launch an experiment leaderboard alongside their notebooks to track, sort, and rank all the experiments. Amazon SageMaker Studio supports many popular frameworks for deep learning such as TensorFlow, Apache MXNet, PyTorch, and more. We are looking for a senior software development engineer to build brand new integrated development editor support offering a variety of development languages and ML technologies.

Key job responsibilities
As a software development/machine learning engineer on the Amazon SageMaker Studio IDE team, you’ll own the Notebook authoring and data scientist IDE experience for AWS ML. You will build/support state-of-the art IDEs on Studio, both web-based and local. Users can choose their preferred IDE on Studio, which will serve as the single place of development environment where users can create experiments, build and evaluate models, debug performance issues, compare experiments, and deploy models. Your team's mission is to provide a highly scalable and collaborative data science workbench where any data scientist, developer, or student can launch a wholly configured and collaborative workspace in the cloud.

A day in the life
You will be responsible for translating business and functional requirements into concrete deliverables with the design, development, testing, and deployment of highly scalable distributed services. You will also partner with other ML teams to help invent, implement, and connect sophisticated algorithms to our cloud based engines. Prior domain knowledge including AI and ML is preferred, though not required. However, strong motivation to learn ML and AI is critical for successful candidates.

Candidates should also be very agile in developing flexible software with respect to scientific, experimentation methods and usage patterns.

Additional responsibilities include:
• Designing, developing and maintaining core system features, services and engines
• Helping define product features, drive the system architecture, and spearhead the best practices that enable a quality product
• Working with external customers, scientists and other engineers to investigate design approaches, prototype new technology, and evaluate technical feasibility
• Operating in an Agile/Scrum environment to deliver high quality software

About the team
Amazon SageMaker is the world’s first fully integrated development environment tailored for machine learning, and is growing rapidly to be the tool of choice for machine learning scientists and practitioners all around the world. SageMaker Studio is our flagship ML IDE for ML development activities including notebooks, experiment management, automatic model creation, debugging, and model and data drift detection. We are looking for talented engineers to build the next generation IDE. We show pride in an inclusive environment that celebrates knowledge sharing, mentorship, and career growth.

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.

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.

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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

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.

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.