Software Development Engineer II, Amazon SageMaker ML Frameworks, AWS Machine Learning Platform
Seattle, Washington, USA
Amazon.com
Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa...Interested in machine learning and developer tools? Amazon SageMaker, Amazon Web Service's (AWS) Machine Learning platform team, is building customer-facing services to help data scientists and developers quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment.
The SageMaker ML Frameworks team builds bridges from the languages and frameworks that data scientists use to SageMaker, with the goal of providing a world class user experience for machine learning development and deployment. This includes a suite of open-source projects that make it easier to use SageMaker.
Below are the public GitHub projects we currently own:
* https://github.com/aws/sagemaker-python-sdk
* https://github.com/aws/sagemaker-tensorflow-extensions
* https://github.com/awslabs/amazon-sagemaker-examples
Key job responsibilities
A successful candidate will bring a passion for Python and machine learning, desire to build open-source community and have an industry wide impact, and ability to work within a fast moving environment in a large company to rapidly deliver products that have a broad business impact.
Your work will focus on improving the user experience and usability of our machine learning tools for developers and data scientists. You will define and implement new ground-breaking products; produce comprehensive, usable software documentation; collaborate closely with our partner teams; recommend changes in development, maintenance and system standards; and hire/mentor junior engineers.
We're moving fast, and this is a great team to come to to have a huge impact on AWS and the world's customers we serve!
About the team
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.
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.
* 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.
* Bachelor’s Degree in Computer Science, Computer or Electrical Engineering, or a related field
* Computer Science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis
* Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, CI/CD, 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 complex software systems that have been successfully delivered to customers
* Strong written communication skills
Preferred Qualifications
* Expertise and interest in the Python programming language* Experience with GitHub and interest in open-source software (OSS)
* Experience with AWS (CDK, CodeBuild, CodePipeline, ECR, S3, IAM, CloudWatch, etc.)
* Experience with Jupyter, JupyterLab, or similar
* Experience with Docker containers
* Experience with machine learning, modern deep learning frameworks (such as PyTorch or TensorFlow), data science, and/or statistical analysis tools is a plus
* Master's degree in Computer Science, Computer or Electrical Engineering, or a related field
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.
Tags: Architecture AWS CI/CD Computer Science Deep Learning Docker Engineering GitHub Jupyter Machine Learning ML models Python PyTorch SageMaker SDLC Statistics TensorFlow Testing
Perks/benefits: Career development Conferences Startup environment
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