Deep Learning Inference SDE

East Palo Alto, California, USA

Full Time
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Posted 1 month ago

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.

Neo optimizes machine learning models to perform at up to twice the speed of the original framework with no loss in accuracy. Upload a pre-trained model built with MXNet, TensorFlow, PyTorch, or XGBoost to your S3 bucket, choose your target hardware platform from Intel, NVIDIA, or ARM, and with a single API call, SageMaker Neo optimizes the model, converts it into an executable module, and returns it to your S3 bucket. The free open source Neo runtime uses less than 100th of the space of the framework to run the model on the target hardware.

The SageMaker Neo team is growing rapidly to keep up with growth in customers and their requests. We are hiring well-rounded software developers with backgrounds in machine learning, systems, AI accelerators, and embedded systems. This role focuses on the cloud services.

Join the Amazon SageMaker Neo team to help AWS customers deploy machine learning models in the cloud and 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. You will have a passion for operational excellence, scale, and performance.

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.

Work/Life Balance
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


· 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.
· Experience designing, building, and running a production service at scale
· Performance tuning of service APIs E2E
· Familiarity with security best practices

Preferred Qualifications

· Familiarity with ML operations services such as SageMaker or other industry standards.
· Familiarity with AWS technologies
· 4+ years technical leadership role in machine learning, system security, or related areas
· MS in Computer Science

Job tags: AI AWS Deep Learning Java Machine Learning ML MXNet Open Source PyTorch SageMaker Security TensorFlow XGBoost
Job region(s): North America
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