
Senior Machine Learning Engineer
Skills
Location
Languages
Fluent English
Job Description
We're looking for a collaborative, technically strong Senior Machine Learning Engineer to lead the architecture, development, and deployment of machine learning platforms and production workflows that help advance medicine.
🎯 Responsibilities
- Act as the central technical liaison between project stakeholders and Data Science teams.
- Own the integration and deployment of algorithms and machine learning models into production workflows.
- Design, build, and scale cloud-native and hybrid data and machine learning platforms using MLOps practices.
- Plan, architect, and develop long-term enterprise tooling and infrastructure for machine learning research, training, and evaluation.
- Own end-to-end software and data architecture for Data Science initiatives.
- Independently define, implement, and test complex technical solutions.
- Act as a technical lead and subject matter expert for machine learning platforms.
- Gather requirements from data-focused teams and continuously improve platform capabilities.
- Mentor peers and help foster a culture of engineering excellence.
- Collaborate on complex data projects and navigate evolving technical requirements.
🛠️ Requirements
- Degree in Computer Science, Software Engineering, or a closely related technical field.
- Extensive professional experience in software engineering with Python.
- Deep understanding of application architecture and design patterns.
- Strong commitment to coding best practices, including TDD and ATDD.
- Experience applying rigorous testing strategies and effective version control.
- Strong understanding of complete machine learning workflows and hands-on experience provisioning the infrastructure required to support them.
- Significant experience with storage technologies and their trade-offs, including relational databases, NoSQL databases, and object storage.
- Solid knowledge of and practical experience with HPC (High-Performance Computing).
- Experience with AWS-based data engineering and analytics solutions.
- Deep familiarity with the Python data ecosystem, including NumPy, Pandas, and Scikit-learn.
- Proficiency in Linux environments.
- Hands-on experience with modern data integration, ETL, and MLOps tools.
- Ability to collaborate effectively, work through ambiguity, and mentor others.
➕ Nice to have
- Domain knowledge or a strong interest in the life sciences sector, including sequencing, PCR, bioinformatics, or digital healthcare.
- Experience building, deploying, or working with Large Language Models (LLMs) and agentic systems.
- Official cloud certifications, such as AWS Certified Solutions Architect – Professional.
- Experience working successfully in large, globally distributed, or international enterprise environments.
Location
Grenzacherstrasse, Basel, Switzerland