Emily Chapman
Associate Consultant
Senior Machine Learning Engineer
Basel, Switzerland
Apply by 19 Jul 2025
Job Ref.: BH-54291
Job Description
Start Date: August 1, 2025
Languages: English required; French or Spanish is a plus
Our client is building machine learning solutions to transform how clinical trials are conducted. Our goal is to turn raw sensor data from smartphones into meaningful, quantifiable health measures that help clinicians assess whether a treatment is working—earlier and more accurately.
This work is aimed at improving decision-making during the earliest stages of drug development, ultimately helping pharmaceutical teams reduce R&D timelines and costs.
Looking for one or two senior-level machine learning engineers to join our team in Europe.
The Role We’re looking for senior machine learning engineers who are excited to work with real-world, high-variability sensor data and can design systems that extract meaningful clinical insights. This is a hands-on role, with significant influence on how our models are built, validated, and deployed in production.
This position is ideal for someone who has experience translating research into production-level code, and who is motivated by the opportunity to work at the intersection of machine learning, digital biomarkers, and early-stage clinical research.
Responsibilities
- Develop and deploy machine learning models that process raw time-series data (e.g., from smartphone sensors) into structured, clinically relevant measures.
- Apply techniques such as signal denoising, filtering, and feature extraction to improve model robustness and reliability.
- Collaborate with clinical and research teams to define measurable indicators that are sensitive to changes during treatment.
- Translate exploratory prototypes into production-grade systems that are well-documented, tested, and suitable for regulated environments.
- Mentor and support junior ML scientists, helping shape a consistent and scalable ML approach.
- Contribute to the broader vision of building tools that support more efficient and evidence-driven drug development.
- 5+ years of experience developing machine learning models, ideally in time-series, sensor, or biomedical data.
- Advanced proficiency in Python and experience with multiple ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
- Strong understanding of signal processing and experience working with noisy, real-world data.
- Prior experience working in or alongside regulated or research environments (e.g., pharma, medtech, clinical trials) is a strong advantage.
- Experience deploying ML systems in production, ideally using tools such as Databricks and AWS.
- Based in Europe.
- English fluency required. French or Spanish is a plus.
You’ll join a focused, mission-driven team at an early stage and contribute to building both our models and our culture.