Amazon

Software Development Manager, SageMaker Machine Learning Framework

2 months agoSeattle, WA

DESCRIPTION

In this role, you will build a new AWS service that is going to be trend setting in the machine learning and AI field. This is an area that requires solving the hardest engineering challenges to enable machine learning powered solutions for our customers. As a tier zero Amazon service our solutions have to be scalable, efficient, and fault tolerant. Experience with machine learning systems is preferred, but not required. You will deliver some of our most strategic technical projects, deliver large scalable systems, design new software systems at the cutting edge of distributed database technology and have a significant bottom-line impact on our business and competitive position. In addition to delivering critical software, you will draw from a deep and broad technical expertise to mentor engineers and provide leadership on complex technical issues. This position within the AWS AI team presents a unique and rare opportunity to get in on the ground floor within a fast growing business and help shape the technology, product and the business. A successful candidate will bring deep technical and software expertise, desire to have an industry wide impact and ability to work within a fast moving, startup environment in a large company to rapidly deliver services that have a broad business impact.

About Us
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.

Interested in making an impact on the Machine Learning and AI ecosystem? As an SDE on the Amazon SageMaker Studio Core Platform team, you'll own the core platform (control plane and data plane) for various interactive applications (e.g. JupyterLab). Our team's mission is to enable any interactive application to scale reliably and securely so any data scientist, developer, or student can launch a wholly configured and collaborative workspace in the cloud. You will work in the company of world experts and there are immense learning opportunities.

Engineers on this team get to:
• Develop in multiple layers of the stack including distributed workflows, high throughput data planes, linux networking, and system security.
• Build fundamental primitives in the cloud for enabling data scientists workflows.
• Develop/maintain operational rigor for a fast-growing AWS service.
Note that this is a backend engineering position.

Key Responsibilities:
• 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.
• Engage with customers and other AWS partners
• Serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers
• You'll be well supported with by a group with deep technical chops, including multiple senior and principal engineers.

Interested in Machine Learning? As the SDM for SageMaker Machine Learning Framework team, you'll own the Amazon SageMaker Python SDK is an open source library for training and deploying machine-learned models on Amazon SageMaker.With the SDK, you can train and deploy models using popular deep learning frameworks, algorithms provided by Amazon, or your own algorithms built into SageMaker-compatible Docker images.

The ML Frameworks builds bridges from the languages and frameworks that data scientists work with SageMaker, with the goal of providing a world class user experience to make machine learning easy, stronger, and universal. This includes a suite of open source projects that make it easier to use SageMaker from popular ML Frameworks. Below are the GitHub projects we have (and more to come!):
1. https://github.com/awslabs/amazon-sagemaker-examples
2. https://github.com/aws/sagemaker-python-sdk
3. https://github.com/aws/sagemaker-spark
4. https://github.com/aws/sagemaker-containers
5. https://github.com/aws/sagemaker-tensorflow-container
6. https://github.com/aws/sagemaker-mxnet-container
7. https://github.com/aws/sagemaker-pytorch-container
And this also includes building the ecosystem through integrations with a list of popular open source projects like Airflow and Kubeflow.

A successful candidate will bring a passion for machine learning, ability to define visionary, ground breaking products, desire to build open-source community and have an industry wide impact, and ability to work within a fast moving environment in a large company to rapidly deliver products that have a broad business impact.

You will own the innovation in the space of ML Platforms, building compelling functionality for the Amazon SageMaker Service. As a SDM You will serve as a key technical resource in the full development cycle, from conception to delivery and maintenance.

We're moving fast, and this is a great team to come to to have a huge impact on AWS and the world's customers we serve!

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What is SageMaker?
Amazon SageMaker (https://aws.amazon.com/sagemaker/) is a fully-managed Machine Learning platform that makes it easy to build ML models, manage them, and integrate them with custom applications for batch or online predictions. SageMaker takes away the "heavy-lifting" normally associated with large-scale Machine Learning implementations so that developers and scientists can focus on the truly creative work of modeling and solving the business problem at hand.

Amazon.com is an Equal Opportunity-Affirmative Action Employer Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.

BASIC QUALIFICATIONS

• Bachelor's degree in Computer Science, Computer Engineering or related technical discipline.
• 6+ years of relevant engineering experience.
• 3+ years people management experience.
• Experience with modern programming languages (Java, C#, Python) and open-source technologies.
• Experience with web/mobile technologies (e.g., JavaScript/TypeScript, NodeJS, React, WebPack, HTTP mechanics/performance).

PREFERRED QUALIFICATIONS

• Experience building tools for data scientists or developers.
• Attuned design sense so can collaborate with UX designers and hold a high bar with "backend" SDE's and SDM's.
• Experience with with CI/CD in a frontend context.
• Experience establishing and leveraging web analytics.
• Machine learning knowledge and experience.
• Deep hands-on technical expertise with established skills in designing and developing solutions to complex problems in a full-stack environment.
• Ability to handle multiple competing priorities in a fast-paced environment.
• A deep understanding of software development in a team, and a track record of shipping software on time.
• 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, visit https://www.amazon.jobs/en/disability/us