Define and drive the technical architecture and system design principles for our AI platform and infrastructure
Work in close collaboration with engineering leads to build flexible frameworks and systems for model training, evaluation and inference across different pathology applications
Guide the CTO office, product management and fellow engineering leads through complex decisions by providing expert consultation on feasibility, architecture, trade-offs and risk mitigation strategies, while ensuring alignment with our technical vision
Foster technical alignment across teams by establishing shared architectural principles and best practices, facilitating cross-team design reviews to enable consistent decision-making across domains
Champion technical excellence by leading strategic initiatives that modernize our architecture and reduce technical debt while measuring and improving our technical health metrics
Elevate the technical capabilities of our engineering staff through structured mentoring, workshops and establishing comprehensive technical guidelines that enable teams to make better design decisions
Drive innovation by evaluating emerging technologies, leading proof-of-concept initiatives and building support for strategic technical investments that advance our engineering capabilities while ensuring measurable business value

Advanced degree in a relevant field or extensive work experience
8+ years of industry experience, with at least 2 years as Staff Engineer or an equivalent role
Solid background in data-intensive systems and software architecture, design patterns and clean coding
Expert Python programming and fluency in C/C++ or other low-level language(s)
Experience with designing and implementing large-scale, distributed ML systems and platforms; proven track record of deploying ML models into production environments
Strong knowledge of machine learning fundamentals, experience with deep learning frameworks (e.g. Pytorch and Tensorflow) and state-of-the-art techniques (e.g. generative models)
Deep understanding of cloud technologies (e.g. GCP, AWS), containerization and orchestration (Kubernetes)
Familiarity with MLOps practices and model lifecycle management, complex CI/CD pipelines, infrastructure as code, code, experiment and model versioning tools (e.g. Git, WandB)
Excellent communication skills, able to articulate complex technical concepts to both technical and non-technical stakeholders
Stays up-to-date with technology trends and latest advancements in AI and ML technologies

Cutting-edge AI research and development, with involvement of Charité, TU Berlin and our other partners
Opportunity to take responsibility and grow your role within the startup
Expand your skills by benefitting from our Learning & Development yearly budget of 1,000 € (plus 2 L&D days), language classes and internal development programs
Mentoring program, you’ll learn from great experts
Flexible working hours and teleworking policy
Enjoy your well-deserved time off within our 30 paid vacations days per year
We are family & pet friendly and support flexible parental leave options
Pick a subsidized membership of your choice among public transport, sports and well-being
Enjoy our social gatherings, lunches and off-site events for a fun and inclusive work environment
Optional company pension scheme

Staff Machine Learning Engineer

Key skills