Time since we first saw it
Day 155
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,331 similar postings that came down. Coming down is not always a hire.
Intern Machine Learning
Munich · Munich, Bavaria, Germany
Open 5 months, first seen by us 155 days ago- Pay
- Pay not listed
- Work setting
On-site — work setting source
Location type: On-site
From the employer’s posting- Employment
Internship — employment source
Employment type: Internship
From the employer’s posting- Team
Engineering › Machine Learning — team source
Department: Engineering › Machine Learning
From the employer’s posting
Before you apply
- New graduates
- For current students
Job title: Intern Machine Learning (all genders)
What you’ll work on
Full postingSupport the design and training of ML models on large clinical datasets
Assist integrating LLM, ASR and RAG solutions into medical workflows
Evaluate, benchmark and fine-tune existing models for clinical use
Explore federated machine learning for privacy-preserving training
Help keep AI features in production reliable, performant and high quality
From the employer’s posting
Support the design and training of ML models on large-scale clinical datasets
Assist with the integration of AI-powered solutions (LLMs, ASR, RAG, Embeddings, and more) into real medical workflows
Support the evaluation, benchmarking, and fine-tuning of existing models for clinical use cases
Explore Federated Machine Learning frameworks for privacy-preserving model training
Contribute to the reliability, performance, and quality of AI features in production
What you’ll bring
All qualificationsCore experience
- Currently enrolled in Informatics, Computer Science, or a related field
- Strong coding background, especially in Python
- Exposure to ML frameworks such as PyTorch, HuggingFace, LangChain or Pydantic
- Fluent English
Qualification wording
Currently enrolled in Informatics, Computer Science, or a related field
Strong coding background, especially in Python
Exposure to ML frameworks such as PyTorch, HuggingFace, LangChain, or Pydantic
Fluency in English
About Avelios Medical
Our mission at Avelios is to unlock clinical data to power seamless healthcare operations for better patient care.
In the employer’s words · Read in context · Company website ↗
Posting record
Report an errorOpen 5 monthsWe first saw this posting 155 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 2, 2026155 days ago
- Recorded sightings
- 166
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Mar 12, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Avelios Medical is hiring
3 open jobs
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- Hugging Face
- PyTorch
Where the posting names them
- Currently enrolled in Informatics, Computer Science, or a related field - Strong coding background, especially in Python - Exposure to ML frameworks such as PyTorch, HuggingFace, LangChain, or Pydantic, including LLMs, ASR models, or RAG pipelines with vector databases (e.g. Qdrant)
- Strong coding background, especially in Python - Exposure to ML frameworks such as PyTorch, HuggingFace, LangChain, or Pydantic, including LLMs, ASR models, or RAG pipelines with vector databases (e.g. Qdrant) - Genuine interest in new technologies and their application to real-world challenges
Your next step
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
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- No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.
Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
ABOUT US
Our mission at Avelios is to unlock clinical data to power seamless healthcare operations for better patient care. To do so, we have built a modular software platform that digitizes and optimizes workflows in hospitals with cutting-edge technology in a user-friendly way. With our software, we enable hospitals, doctors & nurses to provide their patients with the best possible care.
We are growing fast and want to keep expanding our team and business to fundamentally digitize healthcare for the better. We appreciate different backgrounds and see diversity as one of our strengths.
THE TEAM AND ROLE
As an Intern Machine Learning (all genders), you will support the integration of intelligent systems into real-world clinical environments. Collaborating with our interdisciplinary development teams, your role will focus on contributing to bringing state-of-the-art models (LLMs, ASR, and more) into production and embedding them directly into Avelios software to improve everyday medical workflows. This is a unique opportunity to shape how AI transforms the way clinicians work.
YOUR RESPONSIBILITIES
Collaborate with our core development team to bring machine learning into production
Support the design and training of ML models on large-scale clinical datasets
Assist with the integration of AI-powered solutions (LLMs, ASR, RAG, Embeddings, and more) into real medical workflows
Support the evaluation, benchmarking, and fine-tuning of existing models for clinical use cases
Explore Federated Machine Learning frameworks for privacy-preserving model training
Collaborate with leading academic and research institutions
Contribute to the reliability, performance, and quality of AI features in production
Leverage access to high-performance computing infrastructure to build robust ML pipelines
YOUR QUALIFICATIONS
Currently enrolled in Informatics, Computer Science, or a related field
Strong coding background, especially in Python
Exposure to ML frameworks such as PyTorch, HuggingFace, LangChain, or Pydantic, including LLMs, ASR models, or RAG pipelines with vector databases (e.g. Qdrant)
Genuine interest in new technologies and their application to real-world challenges
Fluency in English, German is a plus
NICE TO HAVE
GitHub contributions
Publications at top conferences or demonstrated cutting-edge results in applied ML (e.g. Speech Recognition or NLP)
YOUR BENEFITS
Variety in your tasks and the opportunity to take ownership
Flexible working hours
Support for your personal development through continuous learning and feedback and high chances to transition into a full-time role if the collaboration is successful
An international, informal team structure in a motivating start-up atmosphere, allowing you to participate directly in our customer growth story and the overall success of Avelios
Ability to gain valuable hands-on experience in a startup backed by leading international VCs
A monthly meal allowance up to 75 euros, and Corporate Benefits that give you access to discounts from a wide range of providers in various areas
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Munich, Bavaria, Germany
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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