AI Engineer

Clera
München, Germany
3 months ago

Role details

Contract type
Internship / Graduate position
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Microsoft Azure Information Engineering Python (Programming Language) Large Language Models Terraform Data Pipelines Docker

Job description

Join a seed-funded, Y Combinator-backed pharmatech startup building an AI-native platform for pharmaceutical pricing and market access workflows. As an AI Engineer, you’ll own meaningful parts of the AI and data pipelines and grow into a core engineer who shapes scalable AI solutions in real-world pharma contexts. This is a high-ownership role in a fast-moving, startup-minded environment where reliability and real-world impact are central to the mission.

Requirements

Do you have experience in Terraform?, Do you have a Master’s degree?, * At least 2 years of experience (internships included) in ML, data engineering, or a related role.

  • Strong Python skills with a track record of solving non-trivial problems, especially in data pipelines and ML/LLMs.
  • Experience deploying ML/data pipeline features to production and monitoring their performance.
  • Proficiency with Docker, Azure cloud platform, and Terraform for infrastructure and deployment.
  • Experience designing and implementing automated data quality validation and evaluation systems for data and LLM outputs.
  • A genuine care for correctness, reliability, and real-world impact.

Nice to Have:

  • Experience applying AI to pharma or healthcare workflows.
  • Prior startup experience and comfort operating in high-ownership, fast-paced environments.

Benefits & conditions

  • Own and evolve significant parts of the AI and data pipeline infrastructure.
  • Solve complex problems across large-scale AI and data systems.
  • Build end-to-end LLM-powered extraction and transformation pipelines.
  • Implement and maintain automation workflows for crawling, ingestion, and modelling.
  • Develop automated validation and evaluation systems for data quality and LLM outputs.
  • Turn real pharma workflows into AI-native systems.
  • Take full ownership of features from concept through to production.

Apply for this position

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