Vespa.ai
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About
Vespa.ai is a platform for developing and running large-scale enterprise AI applications. It uses big data, RAG, vector search, machine learning and LLMs to deliver fast, precise decisions. Vespa lets you query, organize, and make inferences in vectors, tensors, text and structured data. It scales to billions of data items, thousands of queries per second with sub-100 millisecond latencies. Use cases include search, generative AI (RAG), recommendation, personalization, semi-structured navigation, and personal/private search. Vespa is fully managed with strong security, offers continuous deployment and upgrades, and is proven at scale with customers like Spotify and Yahoo.
Platform
Task
Features
• vector search
• retrieval-augmented generation (rag)
• high availability
• integrated machine-learned model inference
• search in structured data
• lexical search
• visual retrieval-augmented generation
• scaling
Job Opportunities
Client-Facing Site Reliability Engineer
Vespa.ai is a platform for building and running large-scale enterprise AI applications using big data, RAG, vector search, machine learning, and LLMs for fast, precise decisions.
Education Requirements:
Computer Science (or similar) student
Experience Requirements:
Proven experience as a Site Reliability Engineer, DevOps, or similar role.
Strong programming skills
Strong knowledge of system architecture, cloud infrastructure, and networking.
Proficiency in scripting languages (e.g., Python, Bash) and automation tools (e.g., Ansible, Terraform).
Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
Other Requirements:
Familiarity with monitoring and logging tools (e.g., Prometheus, ELK stack).
Excellent problem-solving and troubleshooting skills.
Familiarity with distributed systems
Responsibilities:
System Architecture and Design
Automation and Infrastructure as Code
Monitoring and Incident Response
Capacity Planning and Performance Optimization
Security and Compliance
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2025 Summer Interns
Vespa.ai is a platform for building and running large-scale enterprise AI applications using big data, RAG, vector search, machine learning, and LLMs for fast, precise decisions.
Education Requirements:
Computer Science (or similar) student
Experience Requirements:
Experience with one of: Java, C++, JavaScript, Go, Python
Other Requirements:
Familiarity with performance measurement, analysis and tuning methodologies
Knowledge/experience with GCP, AWS, Azure
Responsibilities:
Use a Large Language Model to generate data for automated tuning of search and recommendation use cases.
Build user interfaces using Mantine/TypeScript or FastHTML/Python to manage large clusters of nodes.
Build tools in JavaScript/Python for detailed trace analysis of millisecond query performance, with performance optimization hints.
Implement an automated relevance toolkit for Hybrid Search, train models to balance ranking profiles: BM25, vector search ++
Use LangChain or Vercel AI SDK with Vespa and build a full-stack demo application to implement Retrieval Augmented Generation like search.vespa.ai.
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