Senior Applied Scientist, Kumo

At AWS we use Artificial Intelligence to be able to identify every need of a customer across all AWS services before they have to tell us about it and help customers adopt best practices while architecting on the cloud. We are looking for a Senior Applied scientist who will function as a science leader and drive innovation with Gen AI to bring paradigm shift to how the business operates and build best in the world experience that customers will love!

As part of the AWS Applied AI Solutions organization we have a vision to provide business applications leveraging Amazons unique experience and expertise that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazons real-world experience to build opinionated turnkey solutions. Where customers prefer to buy over build we become their trusted partner with solutions that are no-brainers to buy and easy to use.

Some of the science challenges we work on include building Agentic AI systems for complex use cases such as optimizing customers cloud architectures innovating optimization techniques for cost-efficiency in agentic workflows fine-tuning language models for domain specific use cases building scalable agentic evaluation systems designing continual learning systems that incorporate real-time customer and operational feedback to improve model performance over time and developing collaborative filtering approaches that surface personalized recommendations at scale.

You will have an opportunity to lead invent and design technology that will directly impact every customer across all AWS services. We are building industry-leading technology that cuts across a wide range of ML techniques from Natural Language Processing to Deep Learning and Generative Artificial Intelligence. You will be a key driver in taking something from an idea to an experiment to a prototype and finally to a live production system.

As a senior scientist on this team you will define the science vision and long-term research roadmap for your problem space. You will set technical and research direction and ensure our approaches remain at the frontier of whats possible. You will mentor junior scientists and engineers helping them grow their technical depth develop scientific rigor and navigate ambiguous problem spaces. You will raise the bar for the team through code reviews science experimentation reviews and by fostering a culture of experimentation and intellectual curiosity.

Key job responsibilities
-Deliver real world production systems at AWS scale.
-Work closely with the business to understand the problem space identify the opportunities and formulate the problems.
-Use machine learning data mining statistical techniques Generative AI and others to create actionable meaningful and scalable solutions for the business problems.
-Analyze and extract relevant information from large amounts of data and derive useful insights.
-Work with software engineering teams to deliver production systems with your ML models
-Establish scalable efficient automated processes for large scale data analyses model development model validation and model implementation


A day in the life

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

Why AWS
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats 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 its 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
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll 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 theres nothing we cant achieve in the cloud.

Hybrid Work
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible hybrid work model near one of our U.S. Amazon offices.


- PhD or Masters degree and 6 years of applied research experience
- 3 years of building machine learning models for business application experience
- Knowledge of programming languages such as C/C Python Java or Perl
- Experience programming in Java C Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at WA Bellevue - 167100.00 - 226100.00 USD annually