
Senior Artificial Intelligence Engineer
2 weeks ago
We are seeking a highly skilled professional to design, build and scale backend services for our global art information platform.
In this role, you will work on integrating advanced AI/ML models into production systems, powering features such as recommendations, personalization and intelligent search.
This position is ideal for someone passionate about backend engineering and excited to bring AI-powered user experiences to life at scale. Experience in recommendation systems is a strong advantage but not a strict requirement.
Responsibilities:- Service Development: Design, build and maintain robust backend services using Python (FastAPI, Django or Flask).
- AI Model Integration: Integrate machine learning models into production APIs and pipelines for recommendations and personalization.
- Collaboration: Collaborate closely with ML engineers and product teams to deliver AI-driven features.
- Low-Latency APIs: Develop low-latency APIs for serving recommendations and intelligent results.
- Vector Database Integration: Work with vector databases (Qdrant, Pinecone, Elasticsearch etc.) to power similarity search and embeddings.
- Cloud Deployment: Deploy, monitor and scale services in cloud environments (AWS preferred).
- System Architecture: Contribute to system architecture, performance optimization and design decisions.
- CI/CD Pipelines: Implement CI/CD pipelines with strong testing and code quality practices.
- Backend Expertise: Strong understanding of backend architecture and distributed systems.
- Production Experience: Proven track record of building and deploying production-ready APIs.
- AI Integration: Experience integrating ML models or AI services into backend infrastructure.
- Cloud and DevOps: Hands-on expertise with cloud platforms (AWS preferred) and DevOps tools (Docker, Kubernetes, Terraform).
- Database Knowledge: Database expertise: SQL (PostgreSQL/MySQL) and NoSQL (Redis, Elasticsearch).
- Communication Skills: Excellent communication and collaboration skills in remote team settings.
- Recommendation Systems: Experience with recommendation systems or personalization pipelines.
- Vector Databases: Familiarity with vector databases and embedding-based search.
- Frontend Integration: Frontend integration knowledge (React, Next.js, GraphQL).
- Monitoring and Optimization: Experience monitoring and optimizing ML-powered production systems (Prometheus, Grafana).
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