Interested in building ML-distributed systems to deploy machine learning models at scale? With Amazon SageMaker, Amazon Web Service's (AWS) Machine Learning platform team is building customer-facing services to catalyze data scientists and software engineers in their machine learning endeavors. We have set out to build highly scalable and fault tolerant distributed infrastructure to run high performant, low-latency CPU / Deep Learning workloads.
This exciting opportunity is with SageMaker Foundational services team. You will design, implement, test, document, and support cross-cutting services to help customers do machine learning at scale. You will produce reusable and maintainable software using development best practices, and hire/mentor junior development engineers. The best candidates show true end-to-end ownership.
We're moving fast, and this is a great team to join if you want to learn and grow while making a huge impact on AWS and the world's customers we serve!BASIC QUALIFICATIONS
• 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 or related field
• Computer Science fundamentals in object-oriented design
• Computer Science fundamentals in data structures
• Computer Science fundamentals in algorithm design, problem solving, and complexity analysis
• Proficiency in, at least, one modern programming language such as Java, Python, C++, C#, PerlPREFERRED QUALIFICATIONS
• 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.
• Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs.
• Experience with Machine Learning, data mining, and/or statistical analysis tools such as R and MATLAB is a plus
• Master's degree in Computer Science, Computer or Electrical Engineering
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen 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 16 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. This position involves on-call responsibilities, typically three days a month, and also includes solving problems reported by customers. We don't like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don't get paged for the same issue twice.
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.
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, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.
Software and Programming