Interested in Open Source and Machine Learning?
Why will you enjoy this new opportunity? You will be part of the AWS SageMaker open source JupyterLab contribution team, a team of experienced open source developers all over the world. The role will be mainly focused on upstream development on open source projects relevant to tools related to machine learning.
What is the primary need, technical challenge, and/or problem you will be responsible for? A successful candidate will be proficient in core software engineering skills, including debugging, analysis, and problem resolution, writing maintainable software, and translating requirements into implementation. Open source software development is a highly collaborative effort; strong communication skills are required for effective code review, written technical discussions, including advocating for a specific solution to a given problem in a geographically diverse set of contributors.
· Can quickly engage and create meaningful contributions to upstream projects.
· Show expertise in open source development and contribution as well as relevant technical skills in one or more prominent projects.
· Communicate clearly the role of these projects in the context of related projects.
· Same proficiency in design and coding as Software Development Engineers (SDEs), but knowledge and skills are focused on building test and tools
· Proven knowledge of QA concepts and methodology
· Proven track record of delivering genuine excellence in user software testing/writing test automation
· Experience developing test cases that provide confidence in overall quality and help to flush out issues
· Proven ability to work with business and technical teams to understand product vision and requirements
· Proven ability to work with a team of Quality Assurance Engineers (QAEs) and SDETs to ensure the highest quality product delivery
What type of work will you be doing? What assignments, requirements, or skills will you be performing on a regular basis?
· Contribute impactful features to jupyter, jupyterlab, and lumino
· Present your work both internally and externally at conferences, tech talks, and brown bags.
· Coach and mentor internal groups on how to effectively contribute within an open source community.
· Work with SageMaker teams to gather requirements for upstream changes
· Provide support (training, office hours, etc) to internal teams on OSS projects
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.
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 puts a high value on work-live 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.
· Experience building tools for data scientists or developers.
· Experience with OSS contributions in the ML tools space
· Experience with with CI/CD in an OSS context.
· Experience triaging and documenting for OSS
· Machine learning knowledge and experience.
· 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 full-stack development.
· Expert in software quality and testing methodologies/patterns
· Comfortable working in a fast paced, highly collaborative, dynamic work environment
· Experience in communicating with users, other technical teams, and management to collect requirements, evaluate alternatives and develop processes and tools as needed to support the organization.
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.
· Bachelor’s Degree in Computer Science or related field.
· Equivalent experience to a Bachelor's degree based on 3 years of work experience for every 1 year of education
· 3+ years professional experience in software development.
· Knowledge of industry standard test tools and experience in developing product test harnesses and instrumenting products to gather test results
· Experience with test driven development and establishing unit test infrastructures
· Experience with evaluating and integrating open source and in-house developed toolsets