AI Engineer (London)

Qdrant is a leading open-source vector search engine designed for applications powered by embeddings and generative AI. We help developers and enterprises unlock the full potential of semantic search, recommendation systems, and real-time machine learning applications. We are growing fast and looking for passionate, curious, and driven team members who want to help shape the future of AI infrastructure. Tasks We’re looking for a skilled AI Engineer who thrives at the intersection of deep technical development and community collaboration. You’ll play a dual role — driving innovation in AI-driven search and vector database technologies, while also engaging directly with our customers, developer community, and broader AI ecosystem. This is a unique opportunity to combine engineering excellence with external advocacy, helping users succeed while influencing the direction of our product and community. Engineering Design, develop, and optimize AI/ML features in Qdrant ’s core engine and SDKs. Prototype and implement integrations with popular ML frameworks (e.g., Hugging Face, OpenAI, LangChain). Analyze performance, identify bottlenecks, and implement scalable solutions in real-world AI pipelines. Collaborate with product and engineering teams to define and deliver impactful features. Community & Customer Engagement Support developers and users via GitHub, Discord, and other community channels. Communicate complex technical concepts clearly in customer calls, demos, and onboarding sessions. Represent Qdrant at conferences, meetups, and webinars — both as a speaker and technical expert. Create educational content such as blog posts, tutorials, sample projects, and documentation. Collect feedback and insights from the community to inform product development. Requirements Strong proficiency in Python. Solid understanding of machine learning concepts, embeddings, and vector search. Experience with at least one modern ML framework (e.g., PyTorch, TensorFlow, Hugging Face). Excellent communication skills; ability to explain technical topics to diverse audiences. Prior experience contributing to open-source projects or engaging with developer communities. Comfortable presenting and participating in public forums, events, or customer meetings. Bonus Points Contributions to AI infrastructure, vector databases, or search systems. Experience building ML-powered products in production. Knowledge of large language models (LLMs) and retrieval-augmented generation (RAG). Public speaking or published technical content (talks, blog posts, tutorials). Familiarity with the Qdrant ecosystem or similar technologies. Benefits Competitive compensation and equity options. Flexible remote work environment. Opportunity to shape the future of AI infrastructure and open-source tooling. A passionate, transparent, and supportive team. Regular team offsites and conference participation. Please note. This position only for candidates based in London, UK. Originally posted on Himalayas