Machine Learning Engineering

We also believe that AI is a tool, not an identity – without access to high-quality data and a scientifically rigorous, transparent approach to model development, AI is just a buzzword. Aignostics is a spin-off from one of Europe's largest and most prestigious university hospitals (Charité), with employees in Berlin and New York. We work with academic partners as well as leading global life sciences companies.

As a Staff Machine Learning Engineer at Aignostics, you will play a crucial role in shaping the technical direction and architecture of our ML platform and infrastructure. You will work hand in hand with fellow engineering leads at Aignostics, as well as collaborators in academia and industry. Your expertise will be instrumental in driving technical excellence across all ML engineering teams, ensuring we deliver high-quality, scalable solutions that transform complex biomedical data into actionable insights for cancer research and diagnostics. This is a unique opportunity to join a fun, diverse and growing team of 100+ software engineers, applied scientists, biologists and pathologists to shape the next generation of cancer treatments. In our established startup, you have the opportunity to grow personally and technically, take on significant responsibilities and benefit from a dynamic work environment.
We value and celebrate diversity and inclusion and are committed to offering equal employment and promotion opportunities for all applicants and employees. Applicants will be considered regardless of their age, disability, ethnicity, race, gender identity or expression, sexual orientation, religion, etc. Software architect : 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). Machine Learning expertise : Strong knowledge of machine learning fundamentals, experience with deep learning frameworks (e.g. proven track record of deploying ML models into production environments, including performance monitoring (e.g. detection of data drift).
Gained experience in data storage, management and processing at scale. Contribute to open-source projects and technical publications.
Worked in a regulated environment, e.g. financial services, aerospace or healthcare.
Have knowledge of digital pathology or experience with working with biomedical data.

Join a purpose-driven start up: We are working collectively to fight cancer and improve patient outcomes. Work with a welcoming, diverse and highly international team of colleagues
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
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
Enjoy our social gatherings, lunches and off-site events for a fun and inclusive work environment
Optional company pension scheme