Machine Learning Engineer - Wearables & Sensor Data (m/w/d) 80-100%
greenteg AG offers high-tech thermal sensing solutions for an international customer base.
Besides marketing industrial sensors for laser power metering and for assessing insulation properties of buildings, we also offer a unique core body temperature measurement solution (CALERA®) for wearable devices. The technology empowers customers with a wide range of innovative applications such as improving sports performance, continuous and non-invasive patient monitoring, ovulation tracking, sleep analysis or early detection of diseases.
The company develops, manufactures, and markets all solutions at our headquarters in Zürich-Rümlang, where interdisciplinary teams collaborate closely across hardware engineering, embedded systems, and machine learning.
Location: Rümlang, SwitzerlandWorkload: 80–100%
Start Date: Immediately or upon agreement.
Important Note: You will receive a link with the confirmation email to fill out a form. We will not process your application if you fail to fill out the form.
Tasks
To strengthen our R&D team, we are seeking a Machine Learning Engineer – Wearables & Sensor Data to design, implement, and optimise Python-based machine learning pipelines and algorithms that power our wearable sensing technology.
Main tasks:
- Develop and validate machine learning algorithms to predict core body temperature and related physiological parameters based on peripheral sensor signals (e.g., heart rate, skin temperature, heat flux).
- Design, implement, and document standardised model training and inference pipelines to ensure reproducibility and traceability
- Manage and maintain datasets and measurement databases to ensure data quality, accessibility, and consistency for model development and evaluation.
- Analyse internal and customer data to assess algorithm performance, identify opportunities for improvement, and deliver clear, analytical reports and recommendations.
- Provide internal consultancy and feedback to product and development teams on algorithm behaviour, feasibility, and performance to guide product enhancements and innovation.
Requirements
Required Qualifications- Master’s degree (or equivalent) in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, Physics, or a related quantitative discipline.
- Minimum of 2 years of relevant industry experience in machine learning or data science development.
- Ability to provide a public or private code repository (e.g., GitHub, GitLab, Bitbucket) showcasing previous Python-based projects, including data analysis, machine learning pipelines, or production-level code.
- Valid swiss work permit / EU citizenship
- Advanced proficiency in Python, with demonstrated experience developing high-quality, maintainable, and efficient code using libraries such as NumPy, SciPy, scikit-learn, TensorFlow, and PyTorch.
- Strong understanding of Python software engineering best practices, including version control (Git), modular code design, testing, and documentation.
- Solid foundation in time-series data analysis and signal processing, with practical Python implementation experience.
- Familiarity with databases and data storage solutions, including experience with time-series databases (e.g., InfluxDB, TimescaleDB, or similar) and efficient handling of high-frequency sensor data.
- Strong knowledge of modern machine learning models and architectures, training workflows, and model evaluation techniques, with a demonstrated ability to stay up to date with emerging methods, tools, and industry best practices.
- Excellent analytical and problem-solving abilities, with a proven track record of translating complex problems into robust Python-driven solutions.
- Strong communication skills, with the ability to present technical concepts, results, and insights clearly to both technical and non-technical audiences.
- Languages: English C1.
Benefits
What we offer:
- 25 annual paid vacation days (at 100% workload).
- A stimulating role in high-tech manufacturing, involving diverse technologies.
- Collaborative participation in enhancing company processes.
- An energetic, young, and international team.
- Flexible worktime, option for 1-2 remote days per week (at 100% workload).
- Regular social events, teambuilding, BBQ, free coffee and snacks.
Interested? – Join us!
Send your application CV and a short cover letter.
Very important!
You will recieve a link with the confirmation email to fill out a form. We will not process your application if you fail to fill out the form.