Your mission
Machine learning, personalized health, and predictive medicine. If these areas resonate with you, join us to work on extremely motivating challenges at Spiden. Spiden 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 indicators, to better manage chronic diseases, to customize critical treatments and, to improve your health.
Using proprietary optical sensors, Spiden is building a cutting-edge biomedical data generation pipeline to power our Machine Learning prediction algorithms. 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 a talented, experienced, voraciously curious, and self-driven ML Engineer to play a central role in building it with great opportunities for growth.
As a Machine Learning Engineer, you will design and develop ML products that involve large-scale data processing using an advanced ML technology stack. You will lead architecture design and ML infrastructure.
In this role, you will be part of the Machine Learning Engineering team working closely with all RnD teams, including Biomedical Science, Biochemistry, Biophotonics, and Electrical Engineering.
Responsibilities
Triage issues and debug/track/resolve them by analyzing the sources of issues and the impact on medical equipment, hardware, network, or service operations and quality
Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency)
Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies
Communicate effectively mainly in person but as well via video conferencing tools, experience with technical reviews, and coordination with external third parties such as partners and suppliers
Progressively, as we transition out of R&D phase to industrialization and product launch, deploy and use various big data technologies and run pilots to design low latency MLOps architectures
Your profile
Minimum Qualification
- Master's degree in Computer Science, a related technical field, or equivalent ML experience.
- 7+ years of experience in writing software working with at least one compiled and one interpreted language such as C, C++, Go, Python, JavaScript, Java, or similar.
- 4+ years of Machine Learning Experience: ML algorithms and architectures, training models, hyperparameter tuning, feature engineering, distributed model training, hosting and deployment of models and ML pipelines using deep learning frameworks such as TensorFlow or PyTorch, etc. Able to whiteboard common components of ML pipelines.
- 2+ years of experience designing and deploying production-grade system architectures for ML
- Experience with scientific analysis packages such as NumPy, SciPy, Pandas, Scikit-learn
- Experience in development using the Google Cloud Platform or another public cloud platform
- High attention to detail and proven ability to manage multiple, competing priorities, being comfortable in a dynamic and sometimes ambiguous environment.
Preferred qualifications
- PhD degree in Computer Science, or equivalent experience in ML
- Strong experience in MLOPs: ML data management (collect, store, manage data), creating training datasets (data labeling, data augmentation, feature engineering, data partitioning, sampling and slicing), building platform for ML model training and development, model deployment (inference constraints, model compression, server and client side ML, evaluation), ML infrastructure monitoring and maintenance, familiarity with architectural choices for ML systems.
- Working under a matrixed organization involving cross-functional, and/or cross-business projects.
- The following qualifications are a plus:
- Experience in the healthcare or pharma industry
- Hands-on experience building containerized DevOps and CI/CD pipelines, microservices and API development
- Experience with Machine Learning at the Edge (optimization, HW accelerators, GPU, distributed computing)
- Experience in Signal Processing
Work/Life Balance
Working at a growing MedTech 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 flexible working hours and encourage you to find your own balance between your work and personal life.
Values and Mission are important at Spiden, as the ultimate goal is to improve people's well-being and we aspire to live that. We will have the chance to discuss value and mission during the interview process.
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. We want you to grow with Spiden.
About us
Spiden 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.
