Want to be part of a mission to make Machine Learning accessible to everyone?
Amazon SageMaker is a fully-managed Machine platform that makes it easy to build models, manage them, and integrate them with custom applications for batch or online predictions. SageMaker Studio is the first fully integrated development environment (IDE) for machine learning. Users can build, train, tune, debug, deploy and monitor ML models - all in a single, unified web-based interface that boosts developer productivity. SageMaker Studio takes away the "heavy-lifting" normally associated with large-scale Machine implementations so that developers and scientists can focus on the truly creative work of modeling and solving the business problem at hand.
As a member of our team, you will own the complete Studio experience and be responsible for building critical user facing features for various customer personas (Data Scientists, Data Engineers, Analysts etc). You'll also be working on the interfaces and architectures that enable our partner teams within SageMaker to quickly and easily develop customer-facing experiences. You will have significant influence on our overall strategy by helping define the features, driving the system front end architecture, and spearheading best practices within and across several other teams.
This role requires deep technical expertise, excellent leadership skills, and ability to hit the ground running. You will be responsible for solving algorithmically complex problems and build features that can scale to millions of requests and deployed globally delivering an exceptional customer experience. To be successful in this role, you will need to have an established background in developing complex front end products, a strong technical ability, solid communication skills, and a motivation to achieve results in a fast-paced environment. As innovators we embrace new technology, you will be empowered to choose the right highly scalable and available technology to solve complex problems.
Within the role, you should expect to:
- Work closely with senior engineers, UX designers, and product managers to design and develop friendly UI experiences.
- Improve and evolve the technical architecture, working closely with engineers and architects both within and outside your team.
- Lead the operational and engineering excellence efforts for the the team.
- Mentor and develop the engineers.
- Collaborate with other SageMaker engineers and managers for features that cut across the organization.
- Engage with customers and other AWS partners.
- Engage with developers contributing to Open Source JupyterLab Project
- Help with hiring.
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.
We'd love to speak with you about an opportunity to work on the Product that enables scientists, engineers, and even hobbyists to develop artificial intelligence and machine learning models in the cloud.
- 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.
- Experience with test driven development and establishing unit test infrastructures
- Experience building tools for data scientists or developers.
- Experience with evaluating and integrating open source and in-house developed toolsets
- 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.