TL;DR
machineMD is a Bern-based medical device company pioneering automated neurodiagnostics through our flagship neos device and oculometrics software. We're hiring a Principal Machine Learning Engineer / Full-Stack Data Scientist to own end-to-end model development - from data pipelines and signal processing to scalable bayesian inference models - and help us bring specialist-level diagnostics into every clinic.
About machineMD
We're on a mission to radically improve the measurement of brain function through standardized, automated, quantitative exams. Our signature product, neos, is the world's first non-invasive neurophtalmoscope for fast, automated assessment of eye movements and pupils. Founded at the University Hospital of Bern, Switzerland, we aim to bring the diagnostic quality of a highly trained tertiary-care specialist into secondary and primary care settings everywhere.
Tasks
As a Principal Machine Learning Engineer / Full-Stack Data Scientist at machineMD, you will:
* End-to-end ML - perform exploratory data analysis, design and implement ETL pipelines, craft signal-processing features, design and train models, and deploy them with robust monitoring.
* Research & Innovation - apply advanced FIR filtering, probabilistic modelling, non-linear correlation analyses and rigorous hypothesis testing to elevate diagnostic accuracy, while preserving full transparency and interpretability.
* Operationalization - optimize Docker images for minimal footprint, ensure Azure resources remain healthy and cost-efficient, and partner with software engineering to integrate new functionality into our product.
* Mentoring & Leadership - coach other engineers, uphold clean-code principles, and conduct systematic code reviews.
What We Look For
* Olympic-level Dedication - you sweat the edges of every algorithm and make it battle-ready for real-world data.
* End-to-end Ownership - you're equally at home in a Jupyter/marimo notebook prototyping hierarchical bayesian models, as you are debugging ETL pipelines.
* Speed & Iteration - you ship prototypes quickly, get clinician feedback and pivot with agility to refine solutions.
* Technical Craft - you have strong opinions (and data to back them) on software engineering best practices, clean-code mantras and apply Nyquist-informed rigor to signal-processing challenges.
* Collaborative Spirit - you thrive in a flat, interdisciplinary team where decision rights are distributed and communication channels are short.
Requirements
* BSc, MSc, or PhD in Computer Science, Electrical Engineering, Data Science, Biomedical Engineering, or a closely related field from ETH, EPFL, FH or an equivalent institution.
* 7+ years of professional Python experience (incl. pandas and/or polars); bonus points for hands-on Rust or Julia.
* Demonstrated mastery of software development, signal processing, machine learning, and statistical methods; bonus points for hands-on experience applying GenAI techniques in production.
* Proven track record of shipping ML models in production (healthcare or other high-stakes domains).
* Fluent English; German and/or French a plus.
Benefits
Working at machineMD
Located in Bern, Switzerland, we thrive on collaborative, in-person energy, while offering the flexibility you need to do your best work.
We are united by the Four Pillars of Integrity: Radical Responsibility, Feeling Our Feelings, Candor and Clear Agreements. These are not just words on a wall; they guide how we:
* Own our choices (Radical Responsibility)
* Name and honour our emotions (Feeling Our Feelings)
* Speak and listen with honesty (Candor)
* Make and keep clear commitments (Clear Agreements)
Living these principles keeps us "whole," fully alive, and brimming with the energy needed to build world-class diagnostic tools.
Life's too short to work on boring stuff. If you want to bring AI to the frontlines of brain-health and laugh along the way, let's talk
Send your CV and a link to your favourite project or repository with a brief explanation of why you like it.
We welcome applications from all qualified individuals regardless of gender, age, background, or orientation. Applicants must have at least a Swiss B work permit.
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