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Amazon

Amazon

Big Tech

Currently tracking 1110 active AI roles, down 16% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$465k (avg $194k).

Hiring
1110 / 1810
Momentum (4w)
↓-219 -16%
1133 opens last 4w · 1352 prior 4w
Salary range · avg $194k
$65k–$465k
USD · disclosed roles only
Tracked since
Oct '24
last role today
Hiring velocityscroll left for older weeks
2 new roles
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Sep 1
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9 new roles
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27 new roles
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72 new roles
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Mar 2
147 new roles
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Apr 6
214 new roles
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334 new roles
May 4
321 new roles
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Jun 1
288 new roles
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29

Amazon has 1472 active AI-related job listings. The company is heavily focused on roles within the "agents" stage, which accounts for 38% of its AI hiring, followed by "application" at 26%. Engineering is the dominant function, with 1172 positions. Over the last 30 days, Amazon has added 667 new AI roles, representing a 74% increase compared to the previous 30-day period. Frequent tech tags include agent_orchestration, model_serving, and multimodal.

Auto-generated from active job postings · last refreshed 2026-05-24

Frequently asked questions

  • What AI roles is Amazon hiring for?

    Amazon currently has 1573 active AI-related roles in our index. The most common open titles are: ML Data Associate-II (9), 2026 Applied Scientist Intern, Amazon University Talent Acquisition (8), AI Data Associate (Dutch) , Artificial General Intelligence Data Services (8), Software Development Engineer, AWS (8), Senior Delivery Consultant - Data , Professional Services, AWSI HCLS (7). Most positions are in Engineering and Research.

  • What stage of AI development does Amazon focus on?

    Amazon's active AI hiring is concentrated in: agents (41%), application (26%), serving infrastructure (13%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.

  • Where is Amazon hiring AI talent?

    Amazon is hiring AI talent in: United States (1023 roles), Canada (59 roles), United Kingdom (47 roles), India (23 roles).

  • What skills does Amazon look for in AI roles?

    Job postings at Amazon most frequently mention: Machine Learning, Generative AI, Large Language Models (LLMs), Software Engineering, Agentic Systems.

  • How many AI roles has Amazon posted recently?

    In the past 30 days, Amazon has posted 696 new AI-related roles.

Jobs (7)

1110 AI · 3122 total active
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AllUnited States · 1196Canada · 73United Kingdom · 51Australia · 26India · 24Spain · 18Belgium · 16Germany · 16Japan · 12Singapore · 11Taiwan · 11China · 8Switzerland · 8Brazil · 7Italy · 7Romania · 7Poland · 6Mexico · 5France · 4Ireland · 4Netherlands · 4South Korea · 4Philippines · 2Sweden · 2Vietnam · 2Egypt · 1Estonia · 1Malaysia · 1New Zealand · 1Portugal · 1Thailand · 1
Sort
AI scoreRecentTitle
TitleStageFunctionLocationFirst seenAI score
Member of Technical Staff - Simulation, Frontier AI Robotics
The role focuses on developing 3D physics-based and photorealistic simulations for training large-scale machine learning models in robotics. This involves creating simulations for reinforcement learning, generating synthetic data, implementing robotics features, and building real-to-sim workflows to minimize sim-to-real gaps. The goal is to support the training of foundation models for robotics.
DataPost-trainResearchSan Francisco, CA6w ago8
Applied Scientist II
The role focuses on developing and applying cutting-edge simulation methodologies for advanced robotics systems, including physics-based simulation, sim-to-real transfer, and machine learning. The goal is to enable rapid development, testing, and validation of robotic systems in complex environments. The role involves fundamental research and real-world development, translating research into scalable simulation capabilities that impact robot design and building.
DataAgent
Research
Sunnyvale, CA
Apr 24
8
Applied Scientist, AGI , AGI Information
This role focuses on advancing knowledge graphs for the LLM era, specifically for LLM grounding and construction pipelines. It involves web-scale knowledge mining, fact verification, multilingual information retrieval, and agent memory over graphs. The primary responsibility is entity resolution for conflating facts from multiple sources into a single graph entity, requiring scalable, generic, and streaming data solutions. The role also touches upon agent memory, suggesting a secondary stage involvement.
DataAgentResearchSunnyvale, CAApr 178
2026 Fall Applied Science Internship - Information & Knowledge Management (Machine Learning) - United States, PhD Student Science Recruiting
This internship focuses on developing systems and frameworks for machine learning asset lifecycle management, leveraging NLP and information retrieval. The role involves research into ML operations and knowledge engineering to enhance Amazon's ML capabilities.
DataPost-trainResearchSeattle, WAApr 168
2026 Fall Research Science Internship - United States, PhD Student Science Recruiting
This role is for a PhD student intern focused on research science at Amazon. The intern will apply advanced statistical techniques and AI/ML technologies to solve complex problems, implement prototypes, and work with large datasets. Responsibilities include data collection, analysis, interpretation, developing and testing hypotheses, documenting findings, and collaborating with team members. The role emphasizes hands-on scientific work, data analysis, experimental design, and computational modeling.
DataResearchSeattle, WAApr 217
Sr. Research Scientist III, WW Sustainability
Seeking a Senior Research Scientist to lead the design and implementation of autonomous experimental research platforms leveraging data science and AI for sustainable materials innovation. This role combines Physical AI with materials chemistry to accelerate discovery and validation, establishing scientific strategy and technical roadmaps for next-generation autonomous capabilities.
DataAgentResearchSeattle, WAApr 157
Applied Scientist
Internship role for MS or PhD students in Speech, Robotics, Computer Vision, or Machine Learning/Deep Learning. Focuses on building large-scale ML systems using large datasets and translating business requirements into prototypes. Involves analyzing and modeling terabytes of text, images, and other data.
DataResearchSeattle, WAMar 277