Applied Scientist, AWS Sagemaker Canvas

Key Skills

C Programming, C++, Deep Learning, Framework, Java Programming, NeurIPS, Python Programming, PyTorch, SQL

Job Description

Job summary

Are you interested in democratizing machine learning? With Amazon SageMaker, Amazon Web Service's (AWS) Machine Learning platform team is building customer-facing services to empower data scientists and software engineers in their machine learning endeavors. Amazon SageMaker Canvas (https://aws.amazon.com/sagemaker/canvas/) allows you to automatically build machine learning models. SageMaker canvas will automatically explore different solutions to find the best model based on the data you provide.

We are hiring well-rounded applied scientists to work on large-scale distributed training of deep learning models. This includes training and inference system design, distributed algorithms, scalable numerical optimization, computational kernels and operators for deep learning accelerators, efficient in-memory data structures for sparse and dynamic graphs, and communication and storage optimizations.

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 of science problems, from conception to delivery and maintenance. You will produce comprehensive, usable software and models documentation; recommend changes in development, maintenance and system standards. You will own delivery of entire piece of the solution and serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers.

We're moving fast, and 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.

See also more information in our internal wiki for prospective candidates: https://w.amazon.com/index.php/AML/Internals/Recruiting#Information_for_Prospective_Candidates.

BASIC QUALIFICATIONS

• S. or Ph.D. degree in Computer Science and Engineering or related disciplines.
• 2+ years of data/applied science experience in high performance computing, deep learning, systems architecture, or related areas.
• 2+ years of hands-on experience in programming language: C/C++, Python

PREFERRED QUALIFICATIONS

• Ph.D. degree in Computer Science and Engineering or related disciplines.
• Specialization in distributed training, distributed systems, numerical optimization, natural language processing, computer vision, or machine learning with at least 2 years of related work experience
• Proven ability to develop and deliver solution to large-scale training.
• Strong software development skills
• Experience working effectively with science, data processing, and software engineering teams
• Proven track record of innovation in creating novel algorithms and advancing the state-of-the-art
• Experience with deep learning frameworks such as Pytorch, TensorFlow, MXNet
• Published and/or presented papers at ICML, NeurIPS, ICLR, NSDI, OSDI, SC, IPDPS, JMLR, PAMI, KDD, SIGIR, WWW, ACL, EMNLP, CVPR, ICCV, or similar top-tier conferences and events.

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.