Senior AI/ML Engineer

Konvo is revolutionizing eCommerce through AI-powered customer interactions that seamlessly blend support and marketing.

We're building intelligent recommendation systems that understand customer preferences, purchase history, and behavioral patterns to deliver personalized product suggestions that drive revenue while enhancing the customer experience.

About the Role

As an ML/AI Engineer specializing in recommendation systems, you'll be instrumental in designing and implementing our next-generation product recommendation engine that powers our AI Agents across customer touchpoints.

• Design and develop an advanced product recommendation engine leveraging vector embeddings, graph relationships, and large language models
• Create algorithms that identify patterns in customer behavior and product relationships
• Implement recommendation strategies across multiple channels (chat, email, SMS)
• Build systems to continuously improve recommendation quality through feedback loops
• Develop personalization features that integrate with our customer data platform
• Collaborate with data scientists to evaluate and optimize recommendation performance
• Work with the broader engineering team to integrate recommendations into our AI Agent platform

Requirements

We're building with cutting-edge AI/ML technologies:

• Graph Database: Neo4j for modeling complex relationships between customers and products

• Vector Database: Qdrant for semantic search and similarity matching

• Large Language Models: Integration with various LLMs for natural language understanding and generation

• Core Stack:

• Python for ML systems

• TypeScript for integration with our core platform

Qualifications

• 3+ years of experience building recommendation systems or similar ML applications
• Strong understanding of machine learning algorithms, particularly collaborative filtering, content-based filtering, and hybrid approaches
• Experience with vector embeddings and semantic search
• Knowledge of graph databases (Neo4j preferred) and their application to recommendation systems
• Familiarity with LLMs and their integration into recommendation workflows
• Experience with vector databases (Qdrant, Pinecone, or similar)
• Proficiency in Python and data science libraries (PyTorch/TensorFlow, scikit-learn, pandas)

Benefits

• Join a small, innovative team with significant product influence
• Work on challenging problems at the intersection of AI, eCommerce, and customer experience
• Collaborate directly with founders from our Berlin office
• Free lunch on Thursdays
• Competitive compensation package including equity
• Flexible work arrangements

Do you meet some but not all requirements?

We prioritize problem-solving ability, creativity, and passion for AI over checking every technical box. If you're excited about building the next generation of intelligent recommendation systems, we want to hear from you.