Interested in Machine Learning? Amazon SageMaker (https://aws.amazon.com/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. SageMaker is a fully managed Machine Learning platform that makes machine learning services ease of use, universal and accessible to variety of enterprise users. Amazon SageMaker Autopilot (https://aws.amazon.com/sagemaker/autopilot/) allows you to automatically build machine learning models. SageMaker Autopilot will automatically explore different solutions to find the best model based on the data you provide.
With Machine Learning, businesses now ask our machines to do more than repetitive, strictly-defined tasks. We are taking it one step further and have begun to ask them to not only learn on their own but to also interpret data and report to the customer before they even knew they needed it. It's a step in history for you to be a part of. You will be building a platform that incorporates best practices and runs advanced algorithms at production scale and reliability. In this role, you will be responsible for architecting, implementing and expanding features, services and core components of a brand new service for AWS.
You will work in a fast-paced environment and do everything from determining priorities and designing features, to re-architecture as necessary, to automated testing, to mentoring and leading others. The best candidates show true end-to-end ownership and ability to deliver results.
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.
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.
• Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
Bachelor's or Ph.D degree in Computer Science or equivalent work experience.
• 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
• Computer Science fundamentals in object-oriented design, data structures, high-performance computing.
• Computer Science fundamentals in algorithm design, complexity analysis, problem solving and diagnosis.
• Proficiency in, at least, one modern programming language such as Java, Python, C/C++, C#, Perl.
• Experience taking projects from scoping requirements through V1 launch and V2 iterations.
• Knowledge of professional software engineering practices and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
• Experience with highly distributed, multi-tenet systems with clear state-full/state-less boundaries.
• Experience with machine learning, deep learning, data mining, and/or statistical analysis tools.
Amazon is committed to a diverse and inclusive workforce. Amazon is an equal opportunity employer and does not discriminate on the basis of race, ethnicity, 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