AmazonPosted 4mo ago

Sr. Applied Scientist, Alexa Excellence AI Ops, Alexa Excellence AI Ops

Sr. Applied Scientist, Alexa Excellence AI Ops, Alexa Excellence AI Ops at Amazon scores 98 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

IN, TN, Chennaiseniorfull-time

AI in this role

tensorflowscikit-learn

ragai-evaluation

We are seeking a Senior Applied Scientist to join the Alexa Availability team within Alexa Excellence. This role leads the research and development of machine learning and statistical models that power Alexa's reliability at massive scale — serving hundreds of millions of customers globally.

The ideal candidate will tackle complex, ambiguous problems spanning time series multivariate modeling, statistical anomaly detection, LLM-based operational intelligence, and adaptive threshold systems. They will design production-grade ML solutions, establish rigorous evaluation frameworks, and ensure AI systems are grounded, reliable, and free from systematic bias — leveraging techniques such as RAG, confidence scoring, knowledge graph integration, and counterfactual testing.

This scientist will partner with engineers, product managers, and operations leaders to translate scientific innovation into production systems that directly impact Alexa's availability worldwide. They will drive the scientific agenda for the team, mentor fellow scientists, and influence the broader Alexa Excellence organization through technical leadership and cross-team collaboration.

Key Focus Areas:

Anomaly detection and predictive failure modeling
Cross-service correlation and LLM-driven operational intelligence
Production ML at the intersection of large-scale distributed systems and applied science
Model reliability, hallucination mitigation, and grounding for operational AI

Key job responsibilities
As a Senior Applied Scientist on the Alexa Availability team, you will lead the research and development of machine learning and statistical models that power Alexa's reliability at scale. You will work on some of the most complex and ambiguous problems in the space — from time series multivariate modeling and statistical anomaly detection to LLM-based operational intelligence and adaptive threshold systems.

A day in the life
You will design and implement production-grade ML solutions, establish rigorous model evaluation frameworks, and ensure our LLM-powered systems are grounded, reliable, and free from systematic bias. You will apply techniques such as Retrieval-Augmented Generation (RAG), confidence scoring, knowledge graph integration, and counterfactual testing to ensure our AI systems make trustworthy operational decisions at scale.
You will partner closely with software engineers, product managers, and operations leaders to translate scientific innovation into production systems that directly impact Alexa's availability for customers worldwide. You will drive the scientific agenda for your team, mentor fellow scientists, and influence the broader Alexa Excellence organization through your technical leadership and cross-team collaboration.

About the team
The Alexa Excellence team is at the heart of delivering a world-class Alexa experience to hundreds of millions of customers globally. Within Alexa Excellence, the Alexa Availability team is responsible for ensuring Alexa is always on, always responsive, and always reliable. We own the systems, signals, and science that detect, diagnose, and drive resolution of availability issues at scale — before customers ever notice.
We are building the next generation of intelligent availability solutions powered by machine learning, large language models, and advanced statistical modeling. Our work spans anomaly detection, predictive failure modeling, cross-service correlation, and LLM-driven operational intelligence — all operating at the scale and reliability bar that Alexa demands. We operate at the intersection of large-scale distributed systems, applied machine learning, and operational excellence, and we are looking for scientists who can bring both deep technical rigor and a bias for production impact.

Basic qualifications

- 3+ years of building machine learning models 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.

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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RagAI EvaluationTensorFlowscikit-learn

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide that one model's output is better than another's for a given task?
What are the limits of TensorFlow that you've run into, and how did you work around them?
What's a project where you used scikit-learn hands-on?
How would you decide a model or AI system is ready to ship?

Adapt your resume

List these exact terms on your resume: Rag, AI Evaluation, TensorFlow, and scikit-learn. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

Want your resume actually rewritten for this job?

The free preview above is everything we have today. A full resume rewrite is not live yet and has no price set. Join the waitlist and we will email you if we open it.