Who we are:
Calico is a research and development company whose mission is to harness advanced technologies to increase our understanding of the biology that controls lifespan. We will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Executing on this mission will require an unprecedented level of interdisciplinary effort and a long-term focus for which funding is already in place.
Calico is seeking a machine learning engineer to develop and productionize computer vision (CV) algorithms and software tools to analyze biological imaging data sets. Such datasets span a variety of dimensionality (2D images, 3D images, videos) and length scales (physiology to microscopy). This person will be part of a cross-functional effort to build a world-class computing and data analysis platform to support research efforts at Calico. Candidates should be comfortable both with implementing and extending known CV algorithms, and with developing novel, scalable methods to solve difficult questions that help further Calico’s mission.
The ideal candidate should be familiar with state-of-the-art computer vision techniques, including, for example, object detection on images and videos. Candidates should have experience implementing, extending, and debugging CV models, and have expertise in designing and building high-leverage data infrastructure and tools. Candidates will leverage autonomy to learn and apply the latest methods from the broader deep learning literature. Candidates should be able to demonstrate a strong ability to communicate ideas and results, and work cross-functionally to execute on complex projects.
- Ph.D. in Computer Science or related technical field, plus 4+ years software industry experience;
OR M.S. in Computer Science or related technical field, plus 7+ years software industry experience
- Experience building and deploying computer vision and video analytics algorithms in instance segmentation, object tracking, 3D object reconstruction, or latent state modelling
- Ability and interest in tracking and applying state-of-the-art techniques in computer vision literature to problems of biological interest
- Experience building visualization tools to debug computer vision models and data processing pipelines
- Expert in TensorFlow and/or PyTorch
- Strong software engineering skills and substantial expertise in Python
- Track record of effective communication and collaboration in a cross-functional environment
- Strong analytical and quantitative skills
Nice to haves:
- Prior experience applying deep learning algorithms to biological problems
- Prior experience with the organization and quality control of large heterogeneous imaging datasets
- Broad prior experience working with domain-specific formats (e.g. DICOM, nifti, Aperio svs, Leica lif), especially in the context of extremely large images and/or high-rank data
- Public recognition in the field, e.g. via scientific publications or success in computer vision competitions
- Degree specialization in computer vision