ML Engineer, AWS QuickSight

AWS Utility Computing (UC) provides product innovations from foundational services such as Amazon s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS s services and features apart in the industry. As a member of the UC organization, you ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.

Interested in applied ML using latest developments in Large Language Models and Natural Language Processing? We are a team creating innovations and working on continuous waves of new products to help our customers in this space. Ask a question on your data and you get an answer in seconds? thats the magic of Q! Amazon Q in QuickSight is a machine learning powered NLQ capability that allows business users to ask any question in natural language about their data and get the answer in seconds. Help us build the next evolution of Generative BI using latest Large Language Models (LLMs) and applied Machine Learning.

As a Machine Learning Engineer, you will be working on projects that are both ambiguous, interesting and involves a high impact to our customers. You will use machine learning to solve real-life problems our customers face and enable them to make data-driven decisions. You will also envision solutions that help our customers understand how Q answers their questions while also creating new avenues for them to further explore their data. The opportunities are endless!
If this is you, we are looking forward to having you join our team and design, build innovative products and help lead a team that is working towards fundamental changes in the industry!
Amazon QuickSight is a fast, cloud-powered BI service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. QuickSight is revolutionizing Business Intelligence by empowering anyone to use the power of machine learning and Amazon AI to enhance their understanding of data.
Inclusive Team Culture



Key job responsibilities
In this role, you will
- Understand business objectives, product requirements and develop ML algorithms that achieve them.
- Build Prototypes, POC to determine feasibility.
- Run experiments to assess performance and improvements.
- Provide ideas and alternatives to drive a product/feature.
- Define data and feature validation strategies
- Deploy models to production systems and operate them including monitoring and troubleshooting


About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn t followed a traditional path, or includes alternative experiences, don t let it stop you from applying.

Why AWS?
Amazon Web Services (AWS) is the world s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating that s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
Here at AWS, it s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth
We re continuously raising our performance bar as we strive to become Earth s Best Employer. That s why you ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there s nothing we can t achieve in the cloud. - 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language