At Aidence, we bring together the brightest artificial intelligence scientists, software engineers, medical and regulatory specialists, and industry experts to shape tomorrow’s healthcare. Our ambition is to help physicians incorporate AI into clinical practice to deliver outstanding care to their patients. We are currently developing a suite of clinical applications for the oncology pathway. Our first solution focuses on the early detection of lung cancer using deep learning algorithms.
Aidence is one of the first to commercialise AI-based imaging diagnostics with active installations in multiple European countries and the first steps to enter the US market. Our company is backed by a consortium of local and international top-tier VC’s.
In almost five years, we have grown to an international team of around 50 highly motivated and purpose-driven people with different backgrounds and personalities. In the first years, our focus was on building the product. With the new investments we recently received, we can further commercialise and deploy our solutions in the healthcare market. This brings a new dynamic within the team, with commercial people working alongside the development team.
Are you a team player, humble and passionate about our purpose? Do you feel excited about being part of a fast-growing start-up that is making a difference in healthcare?
Then please continue reading!
The model development team is in charge of developing and validating all the models that sit at the core of our products. To streamline our current processes (around model training, model performance evaluation, model and data versioning, managing annotations from our in-house annotation tool, etc.), we are looking to bring further development skills and MLOps experience to the team. Joining us as a Python Data Engineer, you will get the chance to optimize pipelines and to reshape current workflows to make us more efficient and future-proof.
- Design and create pipelines to automate model development processes
- Manage model releases and dataset lifecycles
- Work closely with data scientists and software engineers to collect requirements and to integrate workflows
- Collaborate with the full team to make strategic recommendations and improvements to the technology and business
- Advanced Python development skills (at least 4 years of experience)
- Accustomed to test-driven development and CI/CD practice
- Experience with (unstructured) database technology
- Knowledge of cloud infrastructure (GCP)
- Experience in creating computer vision machine learning pipelines
- Knowledge around ever-evolving ecosystem of machine learning tools and libraries
- Strong communication skills
What we value
- Knowledge of GPUs and hardware infrastructure
- Familiarity with relevant libraries/tools (docker, numpy, pandas, scikit-learn, etc.)
- Familiarity with machine learning infrastructure tools (DVC, MLFlow, WandB, ONNX, etc.)
- Affinity with the principles behind computer vision machine/deep learning (tensor operations, linear algebra, etc.)
- Analytical mindset
- Ability to learn from and contribute to the learning of others on a high academic level
- University – Computer Science or Mathematics or similar
Please use the button below to apply.