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Overview
Nations Technologies designs security chips, microcontrollers and analog devices. Its cryptographic processors are used in identity cards, payment terminals and secure modules. The company also supplies general purpose microcontrollers for industrial systems.
Tech stack
Technologies named in job postings at Nations Technologies over the last 12 months, by layer, with the share of postings for each.
Technologies in use
13
Postings analysed
5
Stack modernity
74/100AI adopter
Languages
C++
Python
Java
Verilog
Frameworks & libraries
Keras
TensorFlow
AI & ML
LLM
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Full Nations Technologies tech stack
13 technologies · by team · pay by technology · changes · similar stacks
Growth
Hiring Momentum
48/100
Stable
Open positions
26
0 opened / 0 closed in 30 days
ATS activity
Every ~4 hours
Today
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.
Industrial Engineering
23% ▲
Hardware
15% ▲
Support
15% ▲
AI/ML
12% ▲
Backend
12% ▲
DevOps
8% ▲
Offices
Where the company hires and what each office is for
Cities
8
Hiring now
6
Countries
3
Busiest office
Shenzhen
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Headquarters
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Office with open vacancies
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Shenzhen
China
HQ
18 open roles 18 posted in 90 days 50% engineering
hires for Industrial Engineering, Hardware, AI/ML
Shanghai
China
Regional office
3 open roles 3 posted in 90 days
hires for Support, Marketing, Industrial Engineering
Wuhan
China
2 open roles 2 posted in 90 days 100% engineering
hires for Backend, Hardware
Beijing
China
1 open roles 1 posted in 90 days
hires for Support
Chongqing
China
1 open roles 1 posted in 90 days 100% engineering
hires for AI/ML
Xi'an
China
1 open roles 1 posted in 90 days
hires for Support
Austin
United States
Regional office
美国
7500 Rialto Blvd, Unit 250, Austin, TX 78735, United States of America
Shinagawa
Japan
Regional office
日本
7F, Shinagawa East-One Tower, 2-16-1, Kounan, Minato-Ku, Tokyo, 108-0075, Japan
Jobs
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In office • Full-Time • Shenzhen
Quantization
TensorRT
LLM
Mixture of Experts
Model Distillation
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