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Scalable

Digital care platform scaling healthcare delivery

AI/ML Engineering Intern - AI/ML Engineering

Applied Machine Learning +1Confirmed live in the last 24 hours
InternshipMunich, GermanyNo salary listed

About the Job

Requirements

  • Currently pursuing a Bachelor's or Master's degree in a quantitative discipline such as computer science, machine learning, data science, financial mathematics, engineering, or physics, or a similar field.
  • Have first experience with cloud infrastructure, particularly AWS.
  • Have hands-on experience with Python.
  • Have fundamental knowledge of current LLM frameworks, Retrieval-Augmented Generation, and vector databases such as LangChain, LangGraph, or OpenSearch.
  • Have first-hand experience creating LLM-powered applications, AI agents, tool use, and multi-step reasoning workflows, such as chatbots, information retrieval, or document summarization.
  • Have experience with machine-learning packages in Python, such as pandas, NumPy, scikit-learn, or statsmodels.
  • Be fluent in written and spoken English.
  • Provide a current transcript of records and, if applicable, work references.

Responsibilities

  • Enhance machine-learning/LLMOps and AI-agent infrastructure for model evaluation, testing, and deployment within an AWS environment.
  • Evaluate and implement different LLM frameworks, AI-agent architectures, and third-party APIs.
  • Design and experiment with AI-agent evaluation systems to measure reasoning quality, reliability, and consistency.
  • Support the development and automation of AI-agent systems and Retrieval-Augmented Generation pipelines.
  • Document findings in the internal knowledge base.
  • Contribute to the development, improvement, and automation of machine-learning and data pipelines.
  • Gain experience with industry-critical infrastructure technologies and apply them productively.

Desired Qualifications

  • Have experience with AI-agent or Retrieval-Augmented Generation evaluation systems, such as LLM-as-a-judge, automated scoring pipelines, or Langfuse-based evaluation.
  • Have a good understanding of software-engineering principles, including API development, code versioning, and testing frameworks such as Pytest or FastAPI.
  • Be familiar with end-to-end machine-learning projects.
  • Have experience with Infrastructure as Code, such as Terraform.
  • Have experience with continuous integration and continuous delivery frameworks, such as Jenkins or GitLab CI/CD.

About the Company

Scalable

Digital care platform scaling healthcare delivery

Scalable Care is a digital care platform that uses conversational AI and automation to help organizations deliver healthcare at a larger scale. The system automates routine interactions and workflows to boost the capacity of healthcare teams, create additional revenue streams, and improve patient outcomes. It works by integrating AI-driven chats and automated processes into care delivery, enabling tasks such as triage, scheduling, follow-ups, and other frontline duties to be handled more efficiently. What sets it apart from competitors is its explicit focus on scalable workforce enablement and revenue growth through AI-powered automation, rather than just offering a single tool or interface. The goal is to empower organizations to expand their healthcare capacity, increase earnings, and achieve better health results for patients.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
San Francisco, CA
Founded
2019

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