ML Engineer - Personalization & Recommendation Systems
Krea is hiring an ML Engineer - Personalization & Recommendation Systems in San Francisco, United States. Level rates it ; you can apply on Krea.
Level's read on this job
- On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
- Krea mentions visa sponsorship in this posting.
- Tools and skills the posting cites include PyTorch and JAX.
- Level lists 13 other open roles at Krea.
AI in this role
About Krea
At Krea, we are building next-generation AI creative tools.
We're 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. We recently took this a step forward with the launch of Krea 2, our first foundation model, built completely from scratch for aesthetic diversity and stylistic control, and with Krea 3 - our new image editing model.
We've raised over $83M and are backed by world-class investors such as a16z, Bain Capital, and Abstract. We work full-time and in-person at our waterfront office in San Francisco. We care about creativity: our team includes musicians, designers, visual artists, and engineers.
This role
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
Nice to have
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
Team: Work alongside a world-class team building the future of AI creative tooling
Impact: Significant scope and company-wide impact
Competitive compensation: generous salary & equity packages
Health & wellness: 100% health & 99% dental/vision insurance premiums covered for employees, health FSA accounts, & long-term disability coverage
Time off: Flexible PTO policy
Financial planning: 401k with a 4% company-sponsored match
Meals in the office: breakfast, lunch, dinner - you name it, we'll cover it
Transit: Ubers covered to & from the office
Sponsorship: We're open to sponsoring international visas where we can (e.g., STEM OPT, OPT, H-1B, O-1, E-3).
And more!
Please note the above benefits & perks are for full-time employees
How we rate this
ML Engineer - Personalization & Recommendation Systems at Krea rates 97 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in machine learning engineer jobs at this level
Pay
- Typical machine learning engineer job
- $197k
This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs
Questions you could be asked
- What's a project where you used PyTorch hands-on?
- Walk me through how you've used JAX in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: PyTorch and JAX. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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