As Machine Learning Engineer focused on “Personalization & Recommendations”, you will design and build the application layer that powers this next-generation engine — from user segmentation and clustering to insight generation and personalized, behavior-driven recommendations. This is a hands-on role for someone eager to create something new from the ground up.
Your Role
1. Application Layer Development
Design and build the foundation of Aktiia’s next-generation recommendation engine together with a cross-functional software team (~20 engineers).
2. Dynamic User Modeling
Develop evolving user profiles that adapt continuously as new data and interactions are integrated.
3. Insight Generation
Transform raw signals into clear, personalized, and engaging user-facing experiences.
4. Cross-Domain Adaptation
Leverage proven methods from recommendation-heavy domains (e.g. travel, streaming, commerce) and adapt them to digital health.
5. End-to-End Ownership
Drive projects from prototyping and experimentation through testing, deployment, and iteration in production.
6. Collaboration
Work closely with product, data science, and engineering teams to ensure solutions are robust, user-friendly, and aligned with business goals.
7. Pioneering Role
Help Aktiia apply recommender system principles in a new domain, shaping something that has not been built before.
Your Profile
8. Academic Background
PhD or MSc in Informatics, Mathematics, Physics, Biology,Data Science, Signal Processing or related field.
9. Professional Expertise
4+ years of experience building and deploying recommendation systems in production, with expertise in personalization, clustering, and recommendation logic.
Proven track record generating user-facing insights and iterating recommendation models at scale. Knowledge of reinforcement learning and its application to personalization and recommendation systems.
10. Technical Experience
Strong programming skills in Python with hands-on experience in modern ML/AI frameworks. Skilled in building, validating and deploying ML models. Familiar with data pipelines, cloud and best engineering practices. Experience with large language models (LLMs), including practical use of open-source models, RAG, embeddings, and fine-tuning.
11. Industry Fit
Preferred background in recommendation-driven industries such as travel, streaming, e-commerce, advertising or digital marketing. Ideally from start-ups or mid-sized companies with end-to-end system ownership.
12. Language Skills
English at highly proficient level is a must. French, German or Italian are advantageous.
13. Personality
Hands-on, execution-driven product builder with strong ownership, accountability, and customer focus. On top you are a strong team player!