Software Development Engineer - AWS SageMaker AI/ML Human-in-the-Loop

The Human-in-loop services team builds AWS services and applications that enable the use of human intelligence in Machine Learning. Common use cases include video labeling, 3d point cloud object detection and natural language processing. Successful machine learning models are built on high-quality training data. But the process to create the training data is often expensive, complicated, and time-consuming. Products such as SageMaker Ground Truth and Augmented AI solve the problem using smart crowd-sourcing and Machine Learning technologies thus improving the quality of the training data while reducing the cost.

In this role you will work closely with stakeholders, other engineering managers and product teams to deliver mission-critical, and complex products and features. You will be a critical engineering leader who will lead the architecture and design process, assess risks and effectively mentor team members to improve their skills and raise the bar on software development best practices. You will own the implementation strategy to radically change our product offering in ways that is the least disruptive to our customers yet delivers significantly value iteratively.

This opportunity requires excellent technical, problem-solving, and communication skills. Ideal candidates have extensive experience with agile methodologies of development, have a high team work mentality coupled with a strong bias for action yet always insisting on highest standards. That said, everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that feels more like a startup than a big company.

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.


The Human-in-loop services team builds AWS services and applications that enable the use of human intelligence in Machine Learning. Common use cases include video labeling, 3d point cloud object detection and natural language processing. Successful machine learning models are built on high-quality training data. But the process to create the training data is often expensive, complicated, and time-consuming. Products such as SageMaker Ground Truth and Augmented AI solve the problem using smart crowd-sourcing and Machine Learning technologies thus improving the quality of the training data while reducing the cost.

In this role you will work closely with stakeholders, other engineering managers and product teams to deliver mission-critical, and complex products and features. You will be a critical engineering leader who will lead the architecture and design process, assess risks and effectively mentor team members to improve their skills and raise the bar on software development best practices. You will own the implementation strategy to radically change our product offering in ways that is the least disruptive to our customers yet delivers significantly value iteratively.

This opportunity requires excellent technical, problem-solving, and communication skills. Ideal candidates have extensive experience with agile methodologies of development, have a high team work mentality coupled with a strong bias for action yet always insisting on highest standards. That said, everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that feels more like a startup than a big company.

Basic Qualifications

· Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design

Preferred Qualifications

· MS in machine learning, computer vision, or related field
· Proficiency in at least one modern programming language, e.g. C/C++/Java/Python