Krea jobs, judged for you, free
AI tools and models for making images, video, and other media.
- AI
- San Francisco, United States
- 51–200 people
- Private
Newest at Krea.
- ML Researcher - PosttrainingSan Francisco · Full-time
- ML Researcher - Image / Video DiffusionSan Francisco · Full-time
- Fullstack EngineerSan Francisco · Full-time
- Founding Customer Success ManagerSan Francisco; New York · Full-time
- Product EngineerSan Francisco · Full-time
- Software Engineer, BackendSan Francisco · Full-time
- Creative LeadSan Francisco; Remote · Remote · Full-time
- Motion DesignerSan Francisco; Remote · Remote · Full-time
- CreativeSan Francisco; Remote · Remote · Full-time
- Engineer, Supercomputing & Distributed SystemsSan Francisco · Full-time
- ML Engineer - Personalization & Recommendation SystemsSan Francisco · Full-time
- Machine Learning EngineerSan Francisco · Full-time
The company, in brief.
What they do
Krea is a creative AI platform. It puts more than 150 image, video, audio, and 3D models in one place, with its own foundation models among them. Krea Agent plans and produces creative work from one prompt. Krea 2 is its first foundation image model, built from scratch. Millions of creatives use Krea.
What they value
- Build tools that empower human creativity, not replace it.
- Make AI intuitive and controllable for creatives.
- Care about creativity: the team includes musicians, designers, visual artists, and engineers.
- Iterate fast and execute fast.
- Lean towards action, agency, and independence.
Where they hire
All 12 open roles are in San Francisco. Krea says that it works full-time and in person at its San Francisco office. Three creative roles also list Remote in the United States, and the customer success role also lists New York. Krea says that it is open to sponsoring visas where it can, such as OPT, H-1B, O-1, and E-3.
Teams and roles
The board lists four departments. Research and Engineering have four open roles each. Krea Studio and GTM have two each.
- Research: two ML researchers, one for image and video diffusion models and one for posttraining. There is also a machine learning engineer for training experiments and one who builds personalization and recommendation systems from scratch.
- Engineering: backend, fullstack, and product engineers. The stack is SvelteKit, TypeScript, Python, Postgres, Redis, ClickHouse, Docker, and Kubernetes. Current work includes durable execution for long workflows, the public API, and enterprise features such as audit logs.
- Supercomputing, inside Engineering: one engineer for the infrastructure behind research and inference. The team runs Kubernetes clusters of more than 1,000 GPUs and data pipelines at petabyte scale, and it builds much of this from scratch.
- Krea Studio: a creative and a motion designer. They work with the Creative Director on launch videos, product demos, and social content.
- GTM: a creative lead who runs demos and workshops for enterprise clients, and a founding customer success manager who owns onboarding, adoption, renewals, and expansion.
What they look for
Four postings ask for ownership from start to finish. The backend and product engineer roles put first-principles thinking above knowledge of a specific language or framework. The backend role prefers four to eight years of experience, and the product engineer role asks for four or more. Six of the 12 roles ask for clear communication.
Taste repeats across the board. The creative, creative lead, and product engineer roles ask for a strong point of view on what good creative work looks like. A creative background is a plus for the backend engineer, the product engineer, and the customer success manager. The creative and creative lead roles ask for regular use of AI creative tools, not only Krea. The creative and motion designer roles require a portfolio.
The machine learning engineer and diffusion researcher roles ask for a proven record with image or video models at scale. The two researcher roles also ask for strong PyTorch skills, a background in distributed training, and comfort with underspecified goals. The supercomputing role does not require Kubernetes or ML experience. It hires for an intuition for distributed systems.
Every posting promises salary and equity, but none states a pay range. The postings do not describe the interview steps.
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