Machine Learning on Edge Devices Solutions Architect
About the Job
At AWS AI, we want to make it easy for our customers to deploy machine learning models on any endpoint in the cloud or at the edge. Just as SageMaker provides a complete set of services to simplify the task of building and training a model, Neo provides an inference engine that is designed to run any machine learning model on any hardware. Running machine learning inference on edge devices reduces latency, conserves bandwidth, improves privacy and enables smarter applications, and is a rapidly growing area as smart devices proliferate consumer and industrial applications.
Are you passionate to help customers accelerate their journey with Machine Learning on edge devices? The SageMaker Neo Edge team is building new technology to deliver the most efficient inference on edge devices, coupled with ease of managing these devices. We are looking for a hands on solutions architect to help customers design solutions and onboard to AWS Amazon SageMaker Edge Manager.
You will work directly with customers to understand their use cases, and also work with the core device SDK team in order to ensure a successful on-boarding. You will create proof of concept demonstrations, help onboard customer solutions to Edge Manager, and create and improve sample applications and notebooks. You will obsess over understanding what customer pain points are, and work closely with the development team to close them. You will promote deeper technical integration with other SageMaker services, with an eye for customer experience (CX). Previous embedded systems experience is important because you will be creating POCs on different target platforms using the Edge Manager device side agent.
You will engage with silicon vendors and device makers on enriching their on-device and device management service needs. This includes assisting with presentations and content that accurately reflects the architecture and potential of Edge Manager.
Join the Amazon SageMaker Neo Edge team to help AWS customers deploy machine learning models on edge devices at scale in production. Work on an open source industry-standard compiler and runtime for machine learning that is already deployed on over 20 million devices.
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.
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.
BASIC QUALIFICATIONS· Bachelor's degree in computer science, engineering, mathematics, or related field of study OR 8+ years of professional or military work experience
· 8+ years within specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics)
· 3+ years of design, implementation, or consulting experience in applications and infrastructures
· Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
· Bachelor's Degree in Computer Science or Engineering
· 5+ years of software development experience in an embedded system platform for a shipping product. Hands on experience with multi-threaded software stacks.
· 5+ years C/C++ experience
· 5+ years experience working with customers to help design solutions on embedded and/or full stack technologies.
· 1 year Python experience or similar scripting language
· 2+ years experience doing customer presentations
· 1+ years of software development experience in system security -- encryption, access control, trusted execution, SELinux, container security, or related technologies
PREFERRED QUALIFICATIONS· Familiarity with a Machine Learning framework such as TensorFlow, PyTorch, or MxNet.
· Experience with running inference runtimes on embedded platforms
· Experience generating and interpreting benchmark data
Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
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.