Deep Learning Software Development Manager

• Bachelor's degree in Computer Science, Computer Engineering or equivalent combination of technical education and experience
• 7+ years of software development experience with at least 3 years in a Software Development Manager role.
• 3+ years experience building distributed systems
• 1+ years working directly with customers and 3rd party partners
• A strong track record of project delivery for large, cross-functional projects
• Experience with modern programming languages (Java, C#, Python) and open-source technologies.

At AWS AI, we strive 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 Machine Learning model, Neo compiles any machine learning model on any hardware for the best performance. Edge Manager enables running those models efficiently on Edge devices. This role owns the cloud services for both of these two strategic AWS AI SageMaker services. https://aws.amazon.com/sagemaker/edge-manager/ https://aws.amazon.com/sagemaker/neo/
Neo optimizes machine learning models to perform at up to twice the speed of the original framework with no loss in accuracy. Neo can optimize a pre-trained model built with MXNet, TensorFlow, PyTorch, or XGBoost or multiple other frameworks, to a chosen target hardware platform. The Neo runtime uses less than 100th of the space of the framework to run the model on the target hardware. Amazon SageMaker Edge Manager provides a software agent that runs on edge devices for model inference and a separate cloud service for managing models on edge devices.
You will manage and grow a team of software developers with backgrounds in machine learning, distributed systems, AI accelerators, and 24/7 production operations. You will have a passion for operational excellence, scale, fault tolerance, and performance. This role has a significant and direct impact to the business.

Key Responsibilities:

• Responsible for the overall software development and deployment life cycle
• Execution against project plans and delivery commitments;
• Manage the day-to-day activities of the engineering team within an Agile/Scrum environment
• Manage departmental resources, staffing, mentoring, and enhancing and maintaining a best-of-class engineering team
• Work closely with the engineers to architect and develop the best technical design and approach
• Work with customers and PMs on product road map definition
• Translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture.

Join us to help AWS customers deploy machine learning models in the cloud and on edge devices at scale in production.

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.

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.

• Experience with large scale distributed systems
• Experience building and operating mission critical, highly available (24x7) systems
• Experience with Machine Learning
• Experience building tools for data scientists or developers
• Exceptional customer relationship skills including the ability to discover the true requirements underlying feature requests, recommend alternative technical and business approaches, and lead engineering efforts to meet aggressive timelines with optimal solutions.
• Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to a variety of audiences.

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.