Head of Computer Vision and Machine Learning
The Head of Computer Vision and Machine Learning will lead a team of talented engineers working on CV and data analysis initiatives for Dexterity's robotics systems. This role involves understanding product requirements, creating CV models, large training sets, and robust regression pipelines, with a focus on semantic and instance segmentation. The leader will oversee model architecture, development, and deployment within complex robotics systems.
As the Head of CV and ML, you will be leading a team of highly qualified and talented Machine Learning and Computer Vision engineers working on Dexterity’s computer vision and data analysis initiatives. The role will involve understanding our current products and future requirements and bringing your substantial expertise to augment the products and help us to meet the future requirements. Previous experience leading CV and ML teams to create CV models, large training sets as well as robust regression pipelines is a prerequisite for this role.
We are very interested in expertise around the subfields of semantic segmentation and instance segmentation and you will be involved in keeping up to date with the latest research papers in these areas and implementing them using platforms like PyTorch or TensorFlow. Robotics data also comes in a variety of different forms that are targets for models to help us predict and analyze behaviors emerging from our robotics systems. You will oversee the overall architecture and lead development of the perfect models, in addition to identifying additional opportunities throughout our system that can be solved with machine learning.
In order to thrive in this role you will have significant experience with RGBD datasets and point clouds as they are important to the type of problems you will encounter in robotics. You will have solid experience in writing optimized code in c++ and python and mentoring other developers. You will have experience architecting models, training pipelines and serving infrastructure at scale. The end to end process of gathering and augmenting data, creating balanced training/validation/regression sets, studying the performance of different models and optimizing their quality, and finally deploying and troubleshooting the models as part of a complex robotics system will be under your supervision.
Posted June 11, 2026