Liom Health AG
Machine learning engineer
Freienbach · SZ
- Berufsfeld
- Informatik · Data & Analytics
- Ausbildung
- Keine bestimmte Ausbildung
- Erfahrung
- 2 bis 5 Jahre
- Lohn
- Geschätzt CHF 80’000–110’000 pro Jahr (100 %)
- Schätzung von jopp, nicht aus dem Inserat.
- Erstmals gesehen
- 26. September 2026
- Zuletzt gesehen
- 26. September 2026
About Liom
LIOM is a Swiss deep-tech company building the ultimate health wearable for conscious living – a continuous, needle-free window into your body's chemistry, starting with glucose. Through this, we empower users to make informed lifestyle choices and live healthier and longer lives. Developed in Switzerland over 8+ years by 50+ scientists, validated across 130+ subjects, and protected by 23 patent families.
Your mission
We are looking for a talented Machine Learning Engineer with at least two years of industry experience in the tech sector. The ideal candidate is an expert in modern python and MLOps tools and practices, and has experience in translating research code into production. If you have experience developing and deploying ML models using PyTorch/Jax/TensorFlow, are familiar with tools like VertexAI and are excited about applying your skills to a challenging problem, we want to hear from you!
As a Machine Learning Engineer you will
Develop, and maintain our model, training, and evaluation code and ensure correctness, reproducibility, performance, and maintainability.
Collaborate with researchers and engineers to design, develop, and deploy full ML pipelines both in the cloud and on compute-constrained devices.
Use cloud-based ML platforms such as VertexAI to streamline and scale ML workflows.
Employ MLOps tools for experiment tracking, model evaluation and selection, deployment and monitoring.
A passion for staying at the forefront of machine learning and software engineering and embracing the latest tools and libraries.
Your profile
Required qualifications:
At least 2 years of experience in a Machine Learning Engineering role.
Proficiency in Python, with a strong track record of writing correct, reproducible and maintainable code.
Proficiency in at least one of the main deep learning frameworks PyTorch/Jax/TensorFlow.
Proficiency with MLOps tools for experimental tracking and monitoring, as well as for Hyperparameter Tuning
Familiarity with cloud-based ML platforms, such as VertexAI.
The following qualifications are a plus:
Experience with distributed training using Kubernetes/Ray.
Experience with pipeline orchestration tools such as AirFlow, Prefect or Dagster.
Experience with model quantization and pruning.
Experience in a compiled or language such as C++ or Rust.
IMPORTANT: We cannot sponsor work permits for non-EU / EFTA nationals for this role. Applications that do not fulfill this criteria will be automatically rejected.
We offer
Work/Life Balance
Working at a growing health-tech start-up is demanding and our goals are ambitious, which is why our team puts a strong emphasis on work-life balance. It isn’t about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. Therefore, we offer flexibility when it comes to presence in the office ensuring the right balance between impact at work and your private life. Values and Mission are important at Liom, as the ultimate goal is to improve people's well-being and we aspire to live that. We will have the chance to discuss values and mission during the interview process.
Diversity
With 18 nationalities in the company, we strive to build a diverse and exciting environment. We care about diversity and equal opportunities.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship.
Amazing team!
In this role, you will be part of a team composed of awesome colleagues from which you will have the opportunity to learn a lot professionally, but also enjoy great conversations and fresh and well informed points of view.
Our recruitment process
The interview process consists of three stages:
Introduction video call
Technical Interview
On-site interview