- 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 Engineering or related field
- Solid Computer Science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis
Interested in building ML-distributed systems to deploy machine learning models for inferencing 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 clustering infrastructure for HPC. Specifically, the real-time inference component enables customers deploy ML models at scale to run high performant, low-latency CPU / Deep Learning workloads and monitor the quality of the models and data in production. ML Ops, CICD and A/B testing are in the mix as well for deploying models safely.
You will design, implement, test, document, and support cross-cutting services to help customers do machine learning at scale. You'll assist in gathering and analyzing business and functional requirements, and translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture. You will serve as a key technical resource in the full development cycle, from conception to delivery and maintenance. You will produce comprehensive, usable software documentation; recommend changes in development, maintenance and system standards. You will own delivery of entire piece of the system and serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers. You will do everything from determining priorities and designing features to re-architecture as necessary, automated testing and mentoring others. The best candidates show true end-to-end ownership.
At SageMaker, there are immense learning as well as growth opportunities. This is a great team to come to have a huge impact on AWS and the world's customers we serve!
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.
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.
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.
- Experience building software systems that have been successfully delivered to customers
- 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 defining system architectures and exploring technical tradeoffs
- Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
- Hands-on expertise in building and operating complex distributed systems
- Master's degree in Computer Science, Computer or Electrical Engineering or related field
- Experience building and operating mission critical, highly available (24x7) systems
- Experience with machine learning, data mining, and/or deep learning frameworks is a plus
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.