About kaiko

In cancer care, treatment decisions can take many days—but patients don’t have that time. One of the reasons for delays? Cancer patients' data is scattered across many places: doctor’s notes, medical imagery, genomics data. At kaiko, we are developing AI foundational models to bring this data together and integrate it into clinical workflows, enabling doctors to make faster, more effective treatments decisions.

We also collaborate closely with the leading Dutch cancer research institute (NKI) on multiple AI research projects and a joint clinical validation initiative. In 2025, we plan on expanding our partnerships to even more hospitals.

We raised significant long-term funding and have offices in Zurich and Amsterdam. Over the past year, our team has nearly doubled in size, now comprising 70+ people from 25 countries. Our multidisciplinary team brings expertise in LLM and foundational model development, data science, product management, compliance, growth, and operations.   

About the role

As a Data & Evaluation ML Engineer, you will work on the design and implementation of our evaluation and data pipelines. Evaluation and data scarcity are arguably the hardest challenges we face in the development of foundation models, and you will play a key role in addressing those.

For evaluation this involves designing and building scalable evaluation pipelines for multimodal models, running them, analysing the results and ultimately work together with ML Researchers and domain experts to guide the development of a state-of-the-art foundation model for Oncology.

On the data side, sourcing, curating and quality control of very large volumes of heterogeneous data is critical for the performance of our Foundation Models. You will be expected to design and build scalable data pipelines that incorporate machine learning and other approaches to filter, rate and synthetically generate datasets used for model training by the ML Engineers.

As part of an interdisciplinary R&D team, you will collaborate closely with other Machine Learning Engineers, Scientists, Software Engineers and medical experts, playing a central role in the development of our most advanced models.

You will be based in Zurich or Amsterdam.

Some areas of responsibility

• Research, Design and Development of state-of-the-art evaluation techniques for Large Foundation Models.

• Research, Design and Development of state-of-the-art data curation, generation and quality control pipelines for training and evaluation data.

If you are an experienced ML and data engineer/scientist and are excited about diving deep into medical data to develop the world's best oncology AI models, we think you will love this job. 

Why kaiko 
At kaiko, we believe the best ideas come from collaboration, ownership and ambition. We’ve built a team of international experts where your work has direct impact. Here’s what we value:

• We act like owners: You’ll have the autonomy to set your own goals, make critical decisions, and see the direct impact of your work.

• We thrive on collaboration: You’ll have to approach disagreement with curiosity, build on common ground and create solutions together.

• We work with ambitious people: You’ll be surrounded by people who set high standards for themselves and others, who see obstacles as opportunities, and who are relentless in their work to create better outcomes for patients.

 In addition, we offer:

• An attractive and competitive salary, a good pension plan and 25 vacation days per year.

• Great offsites and team events to strengthen the team and celebrate successes together.

• A EUR 1000 learning and development budget to help you grow.

• Autonomy to do your work the way that works best for you, whether you have a kid or prefer early mornings.

• An annual commuting subsidy.

About you

• Excellent programming skills and extensive experience with ML Frameworks, particularly Pytorch.

• Experience with designing and developing evaluation pipelines and designing experiments.

• Experience with developing data and ML pipelines and conducting experiments.

• Experience with data modalities common in oncology, including pathology, radiology, EHR etc.

• Strong communication skills and ability to collaborate effectively.

• Capacity to present experimental results and technical concepts clearly and concisely.

Nice to have:

• Experience with data orchestrators like Dagster.

• Experience with performance optimisations for large scale data pipelines.

We are excited to gather a broad range of perspectives in our team, as we believe it will help us build better products to support a broader set of people. If you’re excited about us but don’t fit every single qualification, we still encourage you to apply: we’ve had incredible team members join us who didn’t check every box!