We are a new team in AWS' Kumo organisation - a combination of software engineers and AI/ML experts.
Kumo is the software engineering organization that scales AWS' support capabilities. Amazon's mission is to be earth's most customer-centric company and this also applies when it comes to helping our own Amazon employees with their everyday IT Support needs. Our team is innovating for the Amazonian, making the interaction with IT Support as smooth as possible. We achieve this through multiple mechanisms which eliminate root causes altogether, automate issue resolution or point customers towards the optimal troubleshooting steps for their situation. We deliver the support solutions plus the end-user content with instructions to help them self-serve. We employ machine learning solutions on multiple ends to understand our customer's behavior, predict customer's intent, deliver personalized content and automate issue resolution through chatbots.
As an applied scientist on our team, you will help to build the next generation of case routing using artificial intelligence to optimize business metric targets addressing the business challenge of ensuring that the right case gets worked by the right agent within the right time limit whilst meeting the target business success metric. You will develop machine learning models and pipelines, harness and explain rich data at Amazon scale, and provide automated insights to improve case routing that impact millions of customers every day. You will be a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations.
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.Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.Analyze complex support case datasets and metrics to drive insight.Design, build, and deploy effective and innovative ML solutions to optimize case routing.Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production.Drive collaborative research and creative problem solving across science and software engineering team.Propose and validate hypothesis to deliver and direct our product road map.Work with engineers to deliver low latency model predictions to production. BASIC QUALIFICATIONS- 6+ years of building machine learning models or developing algorithms for business application experience.
- PhD, or Master's degree and 6+ years of applied research experience.
- Experience programming in Java, C++, Python or related language.
- Experience with neural deep learning methods and machine learning.
PREFERRED QUALIFICATIONS- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
Posted: January 7, 2025 (Updated 3 days ago)
Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.
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