ML Engineer - Personalization & Recommendation Systems

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.