Senior Machine Learning Engineer (100% - Senior/Principal)

at  Spiden AG

YOUR MISSION

What could you build on top of real-time and non-invasive Glucose monitoring? That is what Liom is all about, and we want to beat Apple at it.
Machine learning, personalized health, and predictive medicine. If these areas resonate with you, join us to work on foundational technologic and scientific challenges at Liom. We are a Swiss MedTech venture with the vision to use state-of-the-art detection techniques to continuously monitor and learn from a wide range of vital indicators, to better manage chronic diseases, to customize critical treatments and, to improve your health.
Using proprietary optical sensors, Liom is building a cutting-edge biomedical data generation pipeline to train medical-grade Machine Learning algorithms to infer glucose transcutaneously from spectral measurements. To achieve our vision, our team and advisory board consist of world experts coming from top academic institutions (ETH, EPFL, Columbia, Princeton, or Harvard among others) and industry leaders (Baxter, Roche, Lonza). We are looking for talented, experienced, voraciously curious, and self-driven professionals to join an A-team of doers: https://t.ly/vmCKi
After 4+ years in R&D phase, we are sprinting towards product development phase to launch to market. Therefore, joining as one of the first 60 permanent employees provides you great opportunities for growth in responsibilities and impact.

QUALIFICATIONS

• Master’s degree in Computer Science, a related technical field, or equivalent ML experience.
• 8+ years of experience in writing software working with at least one compiled and one interpreted language such as Python, JavaScript, Java, Go, C, C++
• 6+ years of Machine Learning Experience in industry developing and deploying ML models in real-world applications.
• Proficiency in software development methodologies, version control systems (e.g., Git), and CI/CD pipelines is essential.
• In-depth understanding of MLOps principles and best practices, including model versioning, continuous integration and deployment of machine learning models, model monitoring, automated retraining, scalability and resource optimization. Experience with MLOps tools such as Kubeflow, MLflow.
• Familiarity with containerization technologies (e.g., Docker, Kubernetes) and infrastructure-as-code tools (e.g., Terraform) is beneficial.
• High attention to detail and proven ability to manage multiple, competing priorities, being comfortable in a dynamic and sometimes ambiguous environment.
• The following qualifications are a plus:
• Experience with distributed computing platforms (e.g., Spark) and cloud-based machine learning services (e.g., AWS SageMaker, Google Cloud Vertex AI )
• Experience with Machine Learning at the Edge (optimization, HW accelerators, GPU, distributed computing)
• Compliance and Governance: Understanding of compliance requirements and governance frameworks relevant to machine learning deployments, such as data privacy regulations (e.g., GDPR, HIPAA) and medical device industry-specific standards would be a plus
  IMPORTANT: we cannot sponsor working permits for non-EU / EFTA nationals for this role. Applications that do not fulfill this criteria will be automatically rejected.

ABOUT US

Liom is a Swiss medtech venture with the vision to use state-of-the-art detection techniques to continuously monitor and learn from a wide range of vital medical indicators, allowing to improve your individual health.

WE ENCOURAGE YOU TO APPLY EVEN IF YOU DO NOT BELIEVE YOU MEET EVERY SINGLE QUALIFICATION.

Not all strong candidates will meet every single requirement as listed. We know that underrepresented groups more often doubt the strength of their candidacy, but we urge you not to exclude yourself prematurely and to still submit an application if you’re excited about this work and think your profile is overall a good fit!
We believe that products like the ones we’re building will have an impact on a very broad set of people, and we strive to include a range of diverse perspectives on our team. We would love to hear from you

As a Sr. Machine Learning Engineer you will build ML Engineering infrastructure needed to deploy a portfolio of ML models and algorithms on our smartwatch and companion mobile Apps. To be effective in this role, you need to effectively interface with Science (ML Scientists, Data Scientists), Product Development (Electrical Engineering, Photonics, Manufacturing) and Product Management, to acquire and smartly embed multi-disciplinary knowledge into our ML Infrastructure.
You will be joining the Machine Learning Research & Engineering team, currently composed by 20 awesome colleagues. You will be working hand-in-hand with an A-team of 3 Software Engineering leaders, coming from the domains of Data, Cloud and App/Web development with a combined 40YOE in tech, plus an amazing and enthusiastic crew of junior engineers.