Agentic AI Intern: Build Autonomous Signal Detection

Nestle SA

Lausanne

Hybrid

CHF 20,000 - 27,000

Full time

20 hours ago
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Job summary

Nestlé Research invites a motivated student or recent graduate to join as Agentic AI Intern. You will explore how Agentic AI and LLMs can enhance digital early warning systems and work with domain experts to build proof-of-concept approaches.

You’ll design autonomous AI agents and workflows for signal detection, extract entities and evidence, and validate outcomes against real-world use cases in a collaborative environment.

Qualifications

  • Student or recent graduate in CS/CE/DS/AI or related field.
  • Strong knowledge of Generative AI and Agentic AI with Python/data skills.
  • Interest in applying AI to scientific/early warning challenges; food safety/chemistry knowledge is a plus.
  • Experience in Unix environments; exposure to knowledge graphs or linked data is beneficial.
  • Strong analytical, problem-solving and collaboration skills.
  • Fluency in English, written and spoken.

Responsibilities

  • Review state-of-the-art research in Agentic AI and autonomous reasoning.
  • Design and develop proof-of-concept autonomous AI agents and workflows.
  • Explore detection of entities, associations and signals from large unstructured data.
  • Define validation strategies for autonomous agent outcomes.
  • Collaborate with domain experts to translate requirements into proofs-of-concept.

Skills

Generative AI
Agentic AI
Python
Data processing

Education

Bachelor/Master in CS/CE/DS/AI

Tools

Unix
Knowledge graphs
Ontology engineering
Linked data

Job description

Nestlé Research invites a motivated student or recent graduate to join as Agentic AI Intern. You will explore how Agentic AI and LLMs can enhance digital early warning systems and work with domain experts to build proof-of-concept approaches.

You’ll design autonomous AI agents and workflows for signal detection, extract entities and evidence, and validate outcomes against real-world use cases in a collaborative environment.

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