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A decade of mathematical certainty: Reflections on the Automated Reasoning Group
In 2016 a small research team at Amazon announced our presence to the world with the launch of the Automated Reasoning Group (ARG). Our vision was bold: use mathematical logic to not just test AWS systems but to prove, with mathematical certainty, that th
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AWS Trainium Frontier competition: Co-design models and kernels on purpose-built AI chips
Modern LLM architectures have co-evolved within a single hardware family. The shapes of our attention mechanisms, the structure of our multilayer perceptrons (MLPs), the choice of numerical formats, and even the granularity of parallelism strategies have
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34 Amazon Research Awards Build on Trainium recipients announced
Build on Trainium is a $110 million credit program focused on AI research and university education aimed to support the next generation of innovation and development on AWS Trainium. The program provides compute credits to novel AI research on Trainium, i
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How controllers from industrial machinery can coordinate multitask machine learning
Training a machine learning model to handle multiple objectives simultaneously is a bit like trying to follow GPS directions to several destinations at once: the routes often conflict, and compromising between them can leave you farther from every destina
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A new benchmark for evaluating patient-facing health AI agents
When a virtual patient in a benchmark scenario tells an AI agent they're feeling feverish, or hopeless, the difference between a safe response and an unsafe one often comes down to clinical design - not just medical knowledge. As healthcare AI shifts from
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Amazon is investing in the Lean Focused Research Organization
We want to tell you about an investment we're making and why we're excited about it. As AI agents increasingly make decisions that move money, approve claims, and operate critical infrastructure, the standard approach to software testing is no longer suff
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Amazon and University of Michigan give robots a sense of touch
From warehouse automation to surgical assistance, many real-world applications depend on robots performing delicate, contact-intensive tasks. Often missing in these situations is the sense of touch: robots need to feel the forces on their fingertips to ma
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Capturing token IDs during agentic interactions for better reinforcement learning
Reinforcement learning (RL) is one of the techniques we use to make language models better at sustained, multistep tasks like writing code, navigating a website, or carrying out a research workflow. The model doesn't act alone in those settings; it's wrap
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How Amazon tracks carbon intensity across its operations
At Amazon, we believe that as our strategy to reach net-zero by 2040 evolves, we need to continue to raise the bar on what and how we measure. Measuring carbon emissions across our entire business is complex, and the tools and methodologies available are
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The fuel of the future is already here: Why TRISO matters
Amazon is investing in next-generation nuclear technology to meet the rising energy demands of AI infrastructure and cloud computing, and at the heart of that technology are tristructural isotropic (TRISO) fuel particles. This is not your grandparents' nu
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Tech stack
Technologies named in job postings at Amazon Science over the last 12 months, by layer, with the share of postings for each.
Technologies in use
30
Postings analysed
6
Stack modernity
75/100AI adopter
Languages
Python
MATLAB
SAS
SQL
Frameworks & libraries
Shiny
PyTorch
Databases
Amazon Redshift
Cloud & platforms
AWS
Tableau
AWS Lambda
AWS Step Functions
AI & ML
LLM
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Full Amazon Science tech stack
30 technologies · by team · pay by technology · changes · similar stacks
Growth
Hiring Momentum
93/100
Scaling fast
Open positions
6
5 opened / 0 closed in 30 days
Hiring Dynamics
+100%
Hiring Focus
The percentage next to each role is its share of the company's job openings over the last 90 days; the arrow shows the shift versus the previous period.
Data Science
83% ▲
Operations
17% ▲
Actively hiring for Data Science (+5 in 30 days)
Activity Timeline
New location: Hyderabad
Oct 2026
New location: Bengaluru
Oct 2026
Added Perl to stack
Oct 2026
Added NLP to stack
Oct 2026
Added GCP to stack
Oct 2026
Added Agile to stack
Oct 2026
Offices
Where the company hires and what each office is for
Cities
1
Hiring now
1
Countries
1
Busiest office
Gurgaon
Gurgaon
India
1 open roles 1 posted in 90 days 100% engineering
hires for AI/ML
Jobs
≈ $21k – $44k per year (Estimated) • In office • Full-Time • 5+ years exp • Hyderabad
Python
SQL
R
MATLAB
SAS
Shiny
AI/ML
Machine Learning
DevOps
AWS
Analytics
Tableau
Apply
≈ $15k – $36k per year (Estimated) • In office • Full-Time • 3+ years exp • Chennai
Python
SQL
Perl
MATLAB
SAS
SPSS
Machine Learning
DevOps
AWS
Analytics
A/B Testing
Apply
≈ $15k – $36k per year (Estimated) • In office • Full-Time • 3+ years exp • Hyderabad
Python
SQL
Perl
MATLAB
SAS
NLP
Machine Learning
DevOps
GCP
Management
Agile
Apply
≈ $23k – $47k per year (Estimated) • In office • Full-Time • 5+ years exp • Bengaluru
Python
SQL
R
MATLAB
SAS
Shiny
Databases
Amazon Redshift
AI/ML
PyTorch
LLM
Amazon SageMaker
Multi-Agent Systems
Machine Learning
DevOps
CI/CD
AWS
Docker
AWS Lambda
Amazon EC2
Amazon S3
AWS Step Functions
Analytics
Tableau
Apply
≈ $16k – $39k per year (Estimated) • In office • Full-Time • 4+ years exp • Bengaluru
Python
SQL
MATLAB
SAS
Machine Learning
Analytics
ETL/ELT
Apply
