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Day 155
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,301 similar postings that came down. Coming down is not always a hire.
Machine Learning Engineer
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
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Engineering › Machine Learning — team source
Department: Engineering › Machine Learning
From the employer’s posting
What you’ll work on
Full postingBring machine learning models into production with the core development team
Design and train ML models on large-scale clinical datasets
Integrate LLM, ASR and RAG solutions into real medical workflows
Evaluate, benchmark and fine-tune models for clinical use cases
Own reliability, performance and quality of AI features in production
From the employer’s posting
Collaborate with our core development team to bring machine learning into production
Design and train ML models on large-scale clinical datasets
Integrate AI-powered solutions (LLMs, ASR, RAG, Embedding, and more in the future) into real medical workflows
Evaluate, benchmark, and fine-tune existing models to fit clinical use cases
Own the reliability, performance, and quality of AI features in production
What you’ll bring
All qualificationsCore experience
- Strong coding background
- Hands-on experience deploying ML systems to production with PyTorch, LangChain and Pydantic
- Experience with LLMs, ASR models and RAG pipelines using vector databases
- Degree in Informatics, Computer Science or related field, or equivalent practical experience
- Fluent English
Qualification wording
Strong coding background
Hands-on experience deploying ML systems to production using PyTorch, LangChain, and Pydantic
including LLMs, ASR models, and RAG pipelines with vector databases (e.g., Qdrant)
Degree in Informatics, Computer Science, or a related field - or equivalent practical experience
Fluency in English
Benefits in the posting
Full benefits wording- Variety in your tasks and the opportunity to take ownership
- Set your own rhythm with flexible working hours and trust-based time tracking
- A monthly meal allowance up to 75 euros, full coverage of the Deutschlandticket, Urban Sports Club or a subsidized Wellpass membership, a bike leasing program and Corporate Benefits that give you access to discounts from a wide range of providers in various areas
From the employer’s posting.
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
- Nov 13, 2025
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.
- PyTorch
Where the posting names them
- Strong coding background - GitHub contributions are a plus - Hands-on experience deploying ML systems to production using PyTorch, LangChain, and Pydantic, including LLMs, ASR models, and RAG pipelines with vector databases (e.g., Qdrant). - Publications at top conferences or demonstrated cutting-edge results in applied ML (e.g., Speech Recognition or NLP) is a plus
Your next step
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
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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 a Machine Learning Engineer (all genders), you will drive the integration of intelligent systems into real-world clinical environments. Collaborating with our interdisciplinary development teams, your role will focus on 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
Design and train ML models on large-scale clinical datasets
Integrate AI-powered solutions (LLMs, ASR, RAG, Embedding, and more in the future) into real medical workflows
Evaluate, benchmark, and fine-tune existing models to fit clinical use cases
Work with Federated Machine Learning frameworks for privacy-preserving model training
Collaborate with leading academic and research institutions
Own the reliability, performance, and quality of AI features in production
Leverage access to high-performance computing infrastructure to build robust ML pipelines
YOUR QUALIFICATIONS
Degree in Informatics, Computer Science, or a related field - or equivalent practical experience
Strong coding background - GitHub contributions are a plus
Hands-on experience deploying ML systems to production using PyTorch, LangChain, and Pydantic, including LLMs, ASR models, and RAG pipelines with vector databases (e.g., Qdrant).
Publications at top conferences or demonstrated cutting-edge results in applied ML (e.g., Speech Recognition or NLP) is a plus
Interest in new technologies and their application to real-world challenges
Fluency in English, German is a plus
YOUR BENEFITS
Variety in your tasks and the opportunity to take ownership
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
Support for your personal development through continuous learning and feedback
Set your own rhythm with flexible working hours and trust-based time tracking
A virtual stock option package (VSOP) that lets you participate in Avelios’ long-term value creation
A monthly meal allowance up to 75 euros, full coverage of the Deutschlandticket, Urban Sports Club or a subsidized Wellpass membership, a bike leasing program and Corporate Benefits that give you access to discounts from a wide range of providers in various areas
Source details
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- Pay
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- Location & working pattern
Munich, Bavaria, Germany
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- Work authorization
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