Front-End Engineer, AWS SageMaker AI/ML Human-in-the-Loop, GroundTruth

Amazon Web Services
 Santa Clara, CA


Job summary

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 image, 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.

We are looking for driven front-end engineers who are excited about our mission to bring Humans and Machines together and solve problems where ML/AI algorithms alone cannot solve the end to end problems. You will design and implement new features, architect new systems, coordinate with other teams, and drive engineering excellence. You will be responsible for improving the usability of Ground Truth Labelling and make them accessible and easy to use. You will use modern, open and closed source tools to deliver the best possible experience and help our customers quickly solve their problems. Ground Truth offers tremendous learning and growth opportunities with a diversity of challenges. Join our team and have an impact on the world by making ML more accessible than ever.

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.

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.

Basic Qualifications

· Bachelor’s Degree in Computer Science or related field.

· Equivalent experience to a Bachelor's degree based on 3 years of work experience for every 1 year of education

· Experience with modern programming languages and open-source technologies.

· Experience with web/mobile technologies (e.g., JavaScript/TypeScript, NodeJS, React, WebPack, HTTP mechanics/performance).

Preffered Qualifications

· Experience with modern front-end libraries and components such as React, Webpack, TypeScript, etc. · Experience with machine learning, deep learning, data mining, and/or statistical analysis tools is a plus.

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