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Vespa.ai

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.

engineeringonsiteTrondheim, NOfull-time

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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Vespa.ai

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.

engineeringonsiteTrondheim, NOpart-time

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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