Search Solutions Architect, Qdrant

• We are seeking an experienced Solution Architect with a strong background in databases, search engines, and machine learning
• Extensive knowledge of database systems and search engines
• Understanding of vector search concepts
• Strong programming skills in languages in Python
• Familiarity with machine learning frameworks
• Experience with cloud platforms and containerization (Docker, Kubernetes)

Desirable

• In this pivotal role, you will collaborate closely with our clients to design and implement innovative solutions leveraging Qdrant's vector database technologies
• You will serve as a technical expert and trusted advisor, guiding clients through the adoption and integration of our products to ensure their success
• Client Collaboration: Engage with clients to understand their technical requirements and business objectives
• Solution Design: Architect scalable and efficient solutions utilizing Qdrant's vector database and cloud offerings
• Technical Expertise: Provide in-depth guidance on best practices for integrating Qdrant's products into existing systems
• Pre-Sales Support: Assist the sales team with technical presentations, demonstrations, and proof-of-concept projects
• Workshops & Training: Lead technical workshops and training sessions for clients and partners
• Cross-Functional Liaison: Act as a bridge between clients and internal teams, including engineering and product development
• Feedback Contribution: Relay client feedback to influence product enhancements and roadmap
• Industry Insight: Stay updated on the latest trends in vector search, machine learning, and database technologies

• Working in a passionate international team
• Flexible working hours
• Company events
• Choose any hardware
• Remote/home office possible
• Relocation and visa support (EU Blue Card)
• A collaborative and supportive work environment with opportunities for growth and advancement
• The chance to make a significant impact on an innovative technology with the potential to reshape industries

Total funding: $39.9m

In many cases, documents may have too few keywords, or queries might be too large for the usual full-text search to provide the desired result. In such cases, the search either finds no intersections or returns a lot of irrelevant results. Qdrant is setting out to solve this problem with a neural network-based semantic search which can be used stand-alone or in conjunction with traditional search.