ML Engineer - Personalization & Recommendation Systems
Builds personalization and recommendation systems from scratch for AI creative tools, modeling user taste and curating feeds. Designs algorithms for generative models to adapt to individual aesthetics, using ML frameworks like PyTorch/JAX.
About the job
Responsibilities
- 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 model and research team to co-design personalization mechanisms that influence how 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.
Requirements
- 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-haves
- 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.
Compensation
- Competitive compensation (75th percentile of market) with meaningful equity.
Skills
PyTorch, JAX, Python, Recommendation Systems, Representation Learning, Deep Learning, Diffusion Models, Embeddings, Similarity Search, Ranking
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