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Krea AI

Krea AI

Multimodal · Real-time AI image generation

Currently tracking 3 active AI roles, down 12% versus the prior 4 weeks. Primary focus: Ship · Engineering.

Hiring
3 / 3
Momentum (4w)
↓-1 -12%
7 opens last 4w · 8 prior 4w
Salary range
—
Tracked since
Jul '25
last role 6w ago
Hiring velocityscroll left for older weeks
3 new roles
Jul 28
2 new roles
Nov 17
1 new role
Dec 15
4 new roles
Jan 5
1 new role
19
2 new roles
Mar 30
1 new role
Apr 20
3 new roles
Jun 8
1 new role
15

Frequently asked questions

  • What AI roles is Krea AI hiring for?

    Krea AI currently has 3 active AI-related roles in our index. The most common open titles are: Engineer, Supercomputing & Distributed Systems, ML Engineer - Personalization & Recommendation Systems, Machine Learning Engineer. Most positions are in Engineering.

  • What stage of AI development does Krea AI focus on?

    Krea AI's active AI hiring is concentrated in: application (33%), pre-training (33%), data (33%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.

  • Where is Krea AI hiring AI talent?

    Krea AI is hiring AI talent in: United States (3 roles).

  • What technologies does Krea AI's AI team work with?

    Job postings at Krea AI most frequently reference: model serving, fine tuning, vision, inference infra, recommender systems.

Jobs (1)

3 AI · 18 total active
FilteredStageData×
Show
Active onlyAI only (≥ 7)
Stage
AllData · 1Pretrain · 1Ship · 1
Function
AllEngineering · 3
Sort
AI scoreRecentTitle
TitleStageFunctionLocationFirst seenAI score
Engineer, Supercomputing & Distributed Systems
The role focuses on building and operating the infrastructure for AI research and inference, including distributed training, large GPU clusters, petabyte-scale data pipelines, custom distributed datastores, job orchestration systems, and streaming pipelines. It involves designing multi-stage data pipelines, managing distributed training and inference on large GPU clusters, scaling workloads, and optimizing dataloaders and networking for large training runs. The role requires strong systems thinking and experience with distributed systems, Python, Kubernetes, and data tools.
DataEngineeringSan Francisco, CAApr 37