ML Engineer - Personalization & Recommendation Systems
krea.ai · San Francisco, California
- Location
- San Francisco, California, United States
- Employment
- Full time
- Level
- Mid level
- Posted
- 17 December
About this role
About Krea
At Krea, we are building next-generation AI creative tools.
We are dedicated to making AI intuitive and controllable for creatives. Our mission is to build tools that empower human creativity, not replace it.
We believe AI is a new medium that allows us to express ourselves through various formats - text, images, video, sound, and even 3D. We're building better, smarter, and more controllable tools to harness this medium.
This Job
We’re looking for an ML Engineer to architect and build Krea’s personalization and recommendation systems from scratch. You’ll have full ownership over how we understand user taste, curate content, and adapt generative models to individual aesthetics.
This is a role at the intersection of recommendation systems, representation learning, and generative image and video tools.
What you’ll do
Architect and build Krea’s personalization and recommendation stack from the ground up, owning the technical direction end to end.
Design algorithms to model user preference and taste, enabling Krea’s models to adapt to individual styles and aesthetics.
Build high-quality, curated feeds that balance exploration, personalization, and aesthetic coherence.
Work directly with the our model and research team to co-design personalization mechanisms that influence how our generative models learn, adapt, and express style.
Contribute to personalized image generation research, with a focus on style, taste and subjective quality.
Collaborate closely with product, design, and research to define what “good personalization” means in a creative context
Take systems from research and prototyping through production, iteration, and continuous improvement
What we’re looking for
Strong experience building recommendation systems or personalized feeds from scratch
Proven ability to design and ship high-quality curated content experiences
Experience working with media-based personalization (image, video preferred; music or other modalities also welcome)
Solid foundations in machine learning, representation learning, and modern deep learning techniques
Strong Python skills and experience with ML frameworks such as PyTorch or JAX.
Ability to operate independently, make architectural decisions, and own complex systems end to end
Bonus points
Experience with large-scale data systems and production ML infrastructure
Prior work on or familiarity with diffusion models or generative image systems
Background in embeddings, similarity search, ranking, or aesthetic evaluation
Interest in creative tools, art, design, or generative media
What we offer
Openness to sponsoring international candidates (e.g., STEM OPT, OPT, H-1B, O-1, E-3).
Work alongside a world-class team building the future of AI creative tooling.
Significant scope and company-wide impact.
Competitive compensation (75th percentile of market) with meaningful equity.
As published by krea.ai. Applications are handled on their site.
Skills this posting mentions
About krea.ai
a real-time ai image generator and editor built for designers to create, remix, and iterate visually
All 13 openings at krea.aiOne click, then it is written
Apply to krea.ai with a resume written for this role.
Queue ML Engineer - Personalization & Recommendation Systems and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in krea.ai’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- 25 sent a week, free
- No card
- Nothing sent until you say so
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Put this to work
Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
Free, no card. Up to 25 applications sent a week, and nothing is sent until you say so.
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